This PDF file contains the front matter associated with SPIE Proceedings Volume 8292, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

Simultaneous Contrast and Assimilation test targets are almost always viewed at high light levels. We measured the appearances of Simultaneous Contrast, Assimilation and other spatial surrounds near absolute rod threshold. Given the very different spatial organizations of receptive fields in rod and cone vision at detection threshold, it is not obvious that these familiar cone-vision spatial effects would be observed at rod light levels. Nevertheless, the spatial experiments showed that these targets have the same changes in appearance as those observed in bright light. Our experiments used very dim candle light that was above threshold for rods and L cones, and below threshold for M and S cones. Although detection threshold experiments show very different spatial organizations for rod and cone vision, we found that spatial contrast experiments gave the same changes of appearance. Neural contrast mechanisms at the lowest end of our visual HDR range are very similar to those at the top of the range in sunlight. This is true for both chromatic and achromatic targets.

A standard practice in high dynamic range imaging is to compose an image through exposure bracketing which captures a series of exposures of the same scene and then combine them together, followed by dynamic rang compression and some color processing steps. Scenes lit by multiple illuminants such as a room with an artificial light source when the sun is shining through the window is an often encountered scenario which offers opportunity for the high dynamic range feature of an image pipeline to show its advantages. Traditional color constancy algorithms estimate a global white point of the scene and then apply color correction based on this estimate, which could exaggerate the difference between the illuminants, making part of the image better and part of the image worse, or compromise the color of the whole scene. In this paper, we propose a method for the color constancy of high dynamic range scenes with multiple illuminants utilizing the inherent difference in their luminance levels to assist the segmentation of the image into differently illuminated portions and apply their corresponding color constancy parameters. Experimental results using two exposures show superior performance of the proposed algorithm compared to traditional algorithms applying global corrections only.

This paper proposes a novel tone mapping method in consideration of human's perception for a high dynamic range (HDR) image with dimidiated luminance and spatial distributions of bright and dark regions. In order to represent an HDR image with a low dynamic range (LDR) display, it is necessary to appropriately compress a dynamic range of HDR image by tone mapping.There are some HDR images which cannot represent the real scene precisely by applying conventional tone mapping methods. In this study, we view an HDR image with dimidiated luminance and spatial distributions of bright and dark regions as a target image for our work,we assume that human's perception dose not feel a sense of discomfort even if a magnitude relationship between luminance values of pixels near the boundary of the regions is reversed, when bright and dark regions are definitely divided according to dimidiated luminance and spatial distributions. Under the assumption, we divide HDR image into bright and dark regions and apply a tone mapping method to each region independently. In experiments, we will show that our tone mapping method produces the image represented by utilizing a dynamic range effectively. In addition, we will confirm that our tone mapping method is useful through subjective evaluation and discuss the features of the HDR images which are supposed to be suitable for the proposed method.

We report on the results of a study investigating the color perception characteristics of people with red-green color confusion. We believe that this is an important step towards achieving Color Universal Design. In Japan, approximately 5% of men and 0.2% of women have red-green confusion. The percentage for men is higher in Europe and the United States; up to 8% in some countries. Red-green confusion involves a perception of colors different from normal color vision. Colors are used as a means of disseminating clear information to people; however, it may be difficult to convey the correct information to people who have red-green confusion. Consequently, colors should be chosen that minimize accidents and that promote more effective communication. In a previous survey, we investigated color categories common to each color vision type, trichromat (C-type color vision), protan (P-type color vision) and deuteran (D-type color vision). In the present study, first, we conducted experiments in order to verify a previous survey of C-type color vision and P-type color vision. Next, we investigated color difference levels within "CIE 1976 L*a*b*" (the CIELAB uniform color space), where neither C-type nor P-type color vision causes accidents under certain conditions (rain maps/contour line levels and graph color legend levels). As a result, we propose a common chromaticity of colors that the two color vision types are able to categorize by means of color names common to C-type color vision. We also offer a proposal to explain perception characteristics of color differences with normal color vision and red-green confusion using the CIELAB uniform color space. This report is a follow-up to SPIE-IS & T / Vol. 7528 7528051-8 and SPIE-IS & T /vol. 7866 78660J-1-8.

The perceived colour of a stimulus depends on the conditions under which it is viewed. For colours employed as an important cue or identifier, such as signage and brand colours, colour reproduction tolerances are critically important. Typically, such stimuli would be judged using a known level of illumination but, in the target environment, the level of illumination used to view the samples may be entirely different. The effect of changes in the viewing condition on the perceptibility and acceptability of small colour differences should be understood when such tolerances and associated viewing conditions, are specified. A series of psychophysical experiments was conducted to determine whether changes in illumination level significantly alter acceptability and perceptibility thresholds of uniform colour stimuli. It was found that perceived colour discrimination thresholds varied by up to 2.0 ΔE₀₀. For the perceptual correlate of hue however, this value could be of significance if the accepted error of colour difference was at the threshold, thereby yielding the possibility of rejection with changes in illumination level. Lightness and chroma on the other hand, exhibited greater tolerance and were less likely to be rejected with illuminance changes.

The two-by-two dot centering model enables predicting the spectral reflectance of color halftones and does not depend on a specific halftoning algorithm. It requires measuring the reflectances of a large number of two-by-two calibration tile patterns. Spectral measurement of hundreds or thousands of tile patterns is cumbersome and time consuming. In order to limit the number of measurements, we estimate the reflectances of a large majority of two-by- two calibration tile patterns from a small subset comprising less than 10% of all tile patterns. Using this subset of measured two-by-two calibration tile patterns, we perform a linear regression in the absorptance space and derive a transformation matrix converting tile pattern colorant surface coverages to absorptances. This transformation matrix enables calculating the absorptance of all remaining two-by-two tile patterns. For a cyan, magenta and yellow print, with 72 two-by-two measured calibration tile patterns, we are able to create a two-by-two dot centering model having an accuracy only slightly below the accuracy of the model with the fully measured set of 1072 two-by-two tile patterns.

The spatial gamut-mapping algorithm (SGMA) overcomes the drawbacks of the widely used color-by-color methods. Spatial gamut mapping can preserve detailed information in original images by performing adaptive gamut mapping in surrounding pixels within the image. However, spatial gamut mapping can result in hue shift and the halo effect. In addition, it only preserves the boundary information outside the color gamut; the resulting gamut-mapped image does not sufficiently preserve the detailed information in the input image. In this paper, we propose an SGMA that utilizes details of the input image. Our approach improves detail that is not effectively represented with conventional spatial gamut mapping. This is done by taking an original image and first implementing gamut mapping of the input image. Then, the details of the input image and gamut-mapped image are extracted. By examining the out-of-gamut region, the details of the input image can be preserved when these values are added to the gamut-mapped image. The resulting image is obtained by clipping out-of-gamut pixels, since these pixels are generated in the process of preserving details. We demonstrated that images obtained using the proposed method are more similar to the input images, compared to images obtained using conventional methods.

Routine color calibration is imperative for medical applications that rely on color fidelity such as digital pathology, endoscopy, and colposcopy. However, commercially available products vary greatly in price and performance with no available evaluation standard. Related studies have used only one or a few displays to evaluate the performance of color calibration kits. We propose the concept of Virtual Display, a universal display platform that emulates the colorimetric response of real displays. A wide-color-gamut display driven by an FPGA is used to emulate the colorimetric response of real display devices. By changing the look-up tables in the FPGA, the virtual display emulates various real displays for testing different color calibration kits. Our experimental data for 6 real displays show that the virtual display can emulate real displays reasonably well. The results demonstrate that the proposed virtual display approach is a fast, economical, and objective method for evaluating the performance of color calibration kits.

High-end monitors based on LCD technology increasingly address wide color gamut implementations featuring precise color calibration within a variety of different color spaces such as extended sRGB or AdobeRGB. However, images are often reconstructed from digitally compressed images files such as JPEG or MPEG where color quality could be questionable. In particular, when such image files are scaled up or zoomed in, different types of image artifacts become visually noticeable. Among these artifacts we find pixel repetition, blockiness, ringing, and color blotching. While pixel repetition and ringing appear due to insufficient adaptation to image context using a static or context adaptive filter kernel in temporal domain, blockiness and ringing occur due to image compression in frequency domain, when image compression factors are significant. In addition, chrominance channels often undergo an even higher compression ratio that amplifies visibility of artifacts such as color blotches. Consequently, we are interested in improving the quality of images to be displayed depending on image zoom factors. We propose to discriminate most relevant visual artifacts using power spectrum analysis in DCT domain as well as kernel based rescaling combined with statistical analysis taking into account characteristic non-stationary behavior of image content and identifiable visual artifacts. A comparative analysis based on some competitive solutions highlights the effectiveness of our approach and identifies its current limitations with regard to wide color gamut representation, primarily due to mathematical uncertainty of the studied artifacts.

Primary selection plays a fundamental role in display design. Primaries affect not only the gamut of colors the systems is able to reproduce, but also, they have an impact on the power consumption and other cost related variables. Using more than the traditional three primaries has been shown to be a versatile way of extending the color gamut, widening the angle view of LCD screens and improving power consumption of displays systems. Adequate selection of primaries requires a trade-off between the multiple benefits the system offers, the costs and the complexity it implies, among other design parameters. The purpose of this work is to present a methodology for optimal design for three primary and multiprimary display systems. We consider the gamut in perceptual spaces, which offer the advantage of an evaluation that correlates with human perception, and determine a design that maximize the gamut volume, constrained to a certain power budget, and analyze the benefits of increasing number of primaries, and their effect on other variables of performance like gamut coverage.

Standardized in 1976 as a uniform color space, CIELAB is extensively utilized in color science and engineering applications. CIELAB provides both a color difference formula and correlates for common perceptual descriptors of color. Deficiencies in both areas are well-known, and based on these known limitations, numerous fixes have been developed yielding alternative color difference formulae that are derived as modifications of the color difference in CIELAB. In addition, several new color appearance spaces have also been proposed as modifications of the basic CIELAB framework. In this paper, we point out other, lesser-known and poorly-appreciated, limitations of CIELAB that occur particularly in the dark regions of color space. We demonstrate via examples, how these limitations not only cause performance compromises but lead to fundamental breakdowns in system optimization and design problems, making CIELAB unusable in these problems. We consider the reasons why these fundamental limitations were overlooked in the original development of CIELAB and analyze the mathematical representations contributing to the undesired behavior. We argue that fundamental new research is required to overcome this dark side of CIELAB; the development of uniform color spaces and new color appearance spaces must be revisited afresh using new experimental data and keeping in mind newer devices and applications.

For the visual system, luminance contrast is a fundamental property of images, and is one of the main inputs of any simulation of visual processing. Many models intended to evaluate visual properties such as image discriminability compute perceived contrast by using contrast sensitivity functions derived from studies of human spatial vision. Such use is of questionable validity even for such applications (i.e. full-reference image quality metrics), but it is usually inappropriate for no-reference image quality measures. In this paper, we outline why the contrast sensitivity functions commonly used are not appropriate in such applications, and why weighting suprathreshold contrasts by any sensitivity function can be misleading. We propose that rather than weighting image contrasts (or contrast differences) by some assumed sensitivity function, it would be more useful for most purposes requiring estimates of perceived contrast or quality to develop an estimate of efficiency: how much of an image is making it past the relevant thresholds.

The first thing a "marketing guy" asks the digital camera engineer is "how many pixels does it have, for we need as many mega pixels as possible since the other guys are killing us with their "umpteen" mega pixel pocket sized digital cameras. And so it goes until the pixels get smaller and smaller in order to inflate the pixel count in the never-ending pixel-wars. These small pixels just are not very good. The truth of the matter is that the most important feature of digital cameras in the last five years is the automatic motion control to stabilize the image on the sensor along with some very sophisticated image processing. All the rest has been hype and some "cool" design. What is the future for digital imaging and what will drive growth of camera sales (not counting the cell phone cameras which totally dominate the market in terms of camera sales) and more importantly after sales profits? Well sit in on the Dark Side of Color and find out what is being done to increase the after sales profits and don't be surprised if has been done long ago in some basement lab of a photographic company and of course, before its time.

This presentation highlights issues relating to the digital capture printing of 2D and 3D artefacts and accurate colour reproduction of 3D objects. There are a range of opportunities and technologies for the scanning and printing of two-dimensional and threedimensional artefacts [1]. A successful approach of Polynomial Texture Mapping (PTM) technique, to create a Reflectance Transformation Image (RTI) [2-4] is being used for the conservation and heritage of artworks as these methods are non invasive or non destructive of fragile artefacts. This approach captures surface detail of twodimensional artworks using a multidimensional approach that by using a hemispherical dome comprising 64 lamps to create an entire surface topography. The benefits of this approach are to provide a highly detailed visualization of the surface of materials and objects.

There is a very long tradition in designing color palettes for various applications, going back to at least the Upanishad. Although color palettes have been influenced by the available colorants, starting with the advent of aniline dyes in the late 1850s there have been few physical limits on the choice of individual colors. This abundance of choices exacerbates the problem of limiting the number of colors in a palette, i.e., in keeping them into a manageable quantity. For example, it is not practical for a car company to offer each model in hundreds of colors. Instead, for each model year a small number of color palettes is offered, each containing the colors for the body, trim, interior, etc. Another example is the fashion industry, where in addition to solid colors there are also patterns, leading to a huge variety of combinations that would be impossible to stock. The traditional solution is that of "color forecasting." Color consultants assess the sentiment or affective state of a target customer class and compare it with new colorants offered by the industry. They assemble a limited color palette, name the colors according to the sentiment, and publish their result. Textile manufacturers will produce fabrics in these colors and fashion designers will design clothes, accessories, and furniture based on these fabrics. Eventually, the media will communicate these forecasts to the consumers, who will be admired by their cohorts when they choose colors from the forecast palette, which by then is widely diffused. The color forecasting business is very labor intensive and difficult, thus for years computer engineers have tried to come up with algorithms to design harmonious color palettes, alas with little commercial success. For example, Johannes Itten's color theory has been implemented many times, but despite Itten's success in the Bauhaus artifacts, the computer tools have been of little utility. Indeed, contrary to the auditory sense, there is no known physiological mechanism sustaining harmony and the term "harmonious" just has the informal meaning of "going well together." We argue that the intellectual flaw resides in the belief that a masterful individual can devise a "perfect methodology" that the engineer can then reduce to practice in a computer program. We suggest that the correct approach is to consider color forecasting as an act of distillation, where a palette is digested from the sentiment of a very large number of people. We describe how this approach can be reduced to an algorithm by replacing the subjective process with a data analytic process.

An image taken under the backlight condition shows that a main object or foreground appears very dark, but a background appears relatively bright since the exposure time of the main object or foreground is relatively shorter than the one of the background due to high luminance from the background. The determination of the backlight image is generally done by luminance histogram analysis since it is believed that the distinct characteristic of the backlight image is a large luminance difference between the foreground and background. However, this conventional detection method may not be adequate for video images since it generally targets on still images. Furthermore, the detection of the backlight image would not be performed well if there are abrupt changes in light, motion, or scenes. Inaccurate detection leads to unnecessary compensation that makes images over-highlighted or flickered, especially when consecutive frames of video have different illumination modes. Since an image taken under normal light conditions may also have the similar luminance characteristics of the backlight image, it would not be sufficient to discriminate between the normal light and backlight image using only luminance information. Therefore, the analysis of chrominance of images is introduced to detect the backlight image more accurately.

Skin tone is the most important color category in memory colors. Reproducing it pleasingly is an important factor in photographic color reproduction. Moving skin colors toward their preferred skin color center improves the skin color preference on photographic color reproduction. Two key factors to successfully enhance skin colors are: a method to detect original skin colors effectively even if they are shifted far away from the regular skin color region, and a method to morph skin colors toward a preferred skin color region properly without introducing artifacts. A method for skin color enhancement presented by the authors in the same conference last year applies a static skin color model for skin color detection, which may miss to detect skin colors that are far away from regular skin tones. In this paper, a new method using the combination of face detection and statistical skin color modeling is proposed to effectively detect skin pixels and to enhance skin colors more effectively.

In this paper we discuss and quantitatively evaluate the mapping of raw sensor chromaticities, i.e., r = R/(R + G+B) and b = B/(R+G+B), into the CIE 1931 xy chromaticity space, with the constraint that solely training chromaticities are being used which have been obtained using a color checker at a certain illumination. The region near the Planckian locus is considered to be most relevant and a least-squares weighting scheme is proposed to minimize the residuals in this region. Furthermore, the Planckian and daylight loci are approximated in the rb raw sensor chromaticity space using color checker chromaticities at three illuminations, those commonly available in light-booths. The effect of daylight emulation compared to the standard daylight illumination is evaluated. In another part of this paper the mapping of rb chromaticities to correlated color temperature is discussed and evaluated. The proposed method is based on a weighted least-squares fit of a 2nd-order 2D polynomial and outperforms two other estimation methods. We present a comprehensive set of simulation results with real measurements of reflectance, sensitivity, and emission spectrums.

Cell-phone display performance (in terms of color quality and optical efficiency) has become a critical factor in creating a positive user experience. As a result, there is a significant amount of effort by cell-phone OEMs to provide a more competitive display solution. This effort is focused on using different display technologies (with significantly different color characteristics) and more sophisticated display processors. In this paper, the results of a mobile-display comparative performance analysis are presented. Three cell-phones from major OEMs are selected and their display performances are measured and quantified. Comparative performance analysis is done using display characteristics such as display color gamut size, RGB-channels crosstalk, RGB tone responses, gray tracking performance, color accuracy, and optical efficiency.

This paper describes a novel implementation of the Retinex algorithm with the exploration of the image done by an ant swarm. In this case the purpose of the ant colony is not the optimization of some constraints but is an alternative way to explore the image content as diffused as possible, with the possibility of tuning the exploration parameters to the image content trying to better approach the Human Visual System behavior. For this reason, we used "termites", instead of ants, to underline the idea of the eager exploration of the image. The paper presents the spatial characteristics of locality and discusses differences in path exploration with other Retinex implementations. Furthermore a psychophysical experiment has been carried out on eight images with 20 observers and results indicate that a termite swarm should investigate a particular region of an image to find the local reference white.

Color quantization algorithms are used to select a small number of colors that can accurately represent the content of a particular image. In this research, we introduce a novel color quantization algorithm which is based on the minimization of a modified L_p norm rather than the more traditional L₂ norm associated with mean square error (MSE). We demonstrate that the L_p optimization approach has two advantages. First, it distributes the colors more uniformly over the regions of the image; and second, the norm's value can be used as an effective criterion for selecting the minimum number of colors necessary to achieve accurate representation of the image. One potential disadvantage of the modified L_p norm criteria is that it could increase the computation of the associated clustering methods. However, we solve this problem by introducing a two stage clustering procedure in which the first stage (pre-clustering) agglomerates the full set of pixels into a relatively large number of discrete colors; and the second stage (post-clustering) performs modified L_p norm minimization using the reduced number of discrete colors resulting from the pre-clustering step. The number of groups used in the post-clustering is then chosen to be the smallest number that achieves a selected threshold value of the normalized L_p norm. This two-stage clustering process dramatically reduces computation by merging together colors before the computationally expensive modified L_p norm minimization is applied.

A method for detecting human skin and identifying the surface condition of it using the three-phase spectral matching imager (3PSMI) is proposed. The 3PSMI produces correlations pixel-wise between the spectrum of an unknown object and an orthonormal pair of known reference spectra by use of the correlation image sensor (CIS), and outputs the result as a complex image at an ordinary video frame rate, thus realizing both real-time operation and high spectral resolution. In order to apply the 3PSMI to human skin, two tasks-discrimination between skin and non-skin objects and evaluation of the degree of suntan and congestion on skin-are considered and methods of generating an orthonormal pair of reference spectra for these tasks are proposed. Experiments on these tasks are carried out on the developed 3PSMI with the reference spectra generated by the proposed methods.

We describe a method of analyzing the appearance of cosmetic foundation applied to the human face. In particular, we focus on the "oily-shine" appearance, which is caused by sebum. A multi-band camera system with six spectral channels is used for the analysis of the oily-shine appearance. As a basic analysis, we examine the optical features of oily-shine by using two artificial skins looking like make-up skin with oily-shine and without oily-shine. We show that oily-shine can be defined as the standard dichromatic reflection model. On the basis of the above findings, we propose a method for detecting oily-shine area. This method involves (1) the extraction candidate areas, and (2) the evaluation of appearance with oily-shine. First, we capture the CIE XYZ tri-stimulus image of an original make-up face by using the multi-band camera and after a few hours later, capture the same face as a test facial image. Second, the candidate areas with oily-shine are extracted by applying the Laplacian operator to luminance Y component of the test facial image. Third, the principal component analysis is performed on the set of luminance and chromaticity (Y, x, y) of each candidate area. Light reflection of oil-shine is regarded as the specular component of the dichromatic reflection. Finally, we determine the existence of oily-shine by comparing specular clusters between the original image and the test image. The proposed method is tested in experiments with subjective assessment for various real make-up facial images.

This paper proposes a method for analyzing the color characteristics of woodblock prints having oil-based ink and rendering realistic images based on camera data. The analysis results of woodblock prints show some characteristic features in comparison with oil paintings: 1) A woodblock print can be divided into several cluster areas, each with similar surface spectral reflectance; and 2) strong specular reflection from the influence of overlapping paints arises only in specific cluster areas. By considering these properties, we develop an effective rendering algorithm by modifying our previous algorithm for oil paintings. A set of surface spectral reflectances of a woodblock print is represented by using only a small number of average surface spectral reflectances and the registered scaling coefficients, whereas the previous algorithm for oil paintings required surface spectral reflectances of high dimension at all pixels. In the rendering process, in order to reproduce the strong specular reflection in specific cluster areas, we use two sets of parameters in the Torrance-Sparrow model for cluster areas with or without strong specular reflection. An experiment on a woodblock printing with oil-based ink was performed to demonstrate the feasibility of the proposed method.

In an ideal situation, a color managed soft proof is generated by the same Raster Image Processor (RIP) that produces the final raster data for printing. In real-world scenarios, this soft proofing capability is often absent. To overcome this limitation, we developed a workflow using the Adobe PDF library for producing color managed soft proofs before incoming jobs from the web are sent to the RIP. This paper discusses color management challenges that presented themselves and how they were addressed. It also highlights a few specific cases where the separation into subsequent color management and transparency blending processes caused unexpected results and how they were dealt with. Such a system can be implemented as a cloud-based solution to provide end-customers with a quick, inexpensive and reasonably accurate preview of print products before the job is submitted.

We present a stochastically seeded halftoning method with parametric control of dot shapes as well as seed placement adaption to local image structure. While the literature on other randomly structured screens (blue noise, green noise, FM) is quite extensive, there is very little discussion on optimization of dot shape for robustness or preferred tile appearance. The halftoning method that we introduce defines dot centers as seeds that are placed, typically in a random high spatial frequency configuration. Spot functions are defined about these randomly placed seeds, where the spot function allows control of dot cluster growth, touch points, cluster angle, and eccentricity. The spot function can also be applied to regular and irregular polygonal halftone tiling. The seed adaption aspect of the halftoning method allows for better edge rendition than conventional isotropic methods.

Except for linear devices like CRTs, color transformations from colorimetric specifications to device coordinates are mostly obtained by measuring a set of samples, inverting the table, and looking up values in the table (including interpolation), and mapping the gamut from input to output device. The accuracy of a transformation is determined by reproducing a second set of samples and measuring the reproduction errors. Accuracy as the average predicted perceptual error is then used as a metric for quality. Accuracy and precision are important metrics in commercial print because a print service provider can charge a higher price for more accurate color, or can widen his tolerances when customers prefer cheap prints. The disadvantage of determining tolerances through averaging perceptual errors is that the colors in the sample sets are independent and this is not necessarily a good correlate of print quality as determined through psychophysics studies. Indeed, images consist of color palettes and the main quality factor is not color fidelity but color integrity. For example, if the divergence of the field of error vectors is zero, color constancy is likely to take over and humans will perceive the color reproduction as being of good quality, even if the average error is relatively large. However, if the errors are small but in random directions, the perceived image quality is poor because the relation among colors is altered. We propose a standard practice to determine tolerance based on the Farnsworth-Munsell 100-hue test (FM-100) for the second set and to evaluate the color transpositions-a metric for color integrity-instead of the color differences. The quality metric is then the FM-100 score. There are industry standards for the tolerances of color judges, and the same tolerances and classification can be use for print workflows or its components (e.g., presses, proofers, displays). We generalize this practice to arbitrary perceptually uniform scales tailored to specific applications and present an implementation. In essence, we propose to extend the color discrimination test procedures used to evaluate human observers, to mechanical and electronic color reproduction devices.

There are several parameters, which influence the characteristics of the final printed colors in digital printing. One of the most important one is the substrate (paper). In the present study, the effect of uncoated papers on the laser printed colors was investigated. For this purpose, three kinds of paper with the same grammage value of 80 and different whiteness and texture were selected. The effect of paper on the printer's reproducibility, light-fastness, color gamut and colorimetric characteristics of the final printed samples were studied for a Canon Laser Printer LBP-5050. It was found out that, the reproducibility of the printer is statistically dependent on the paper's type. The average of color change via exposing light is between 1.3 and 1.8 for different papers. The color difference caused by paper variation illustrates the effect of paper on the final printed colors. The texture properties of the papers were quantified with Edge Frequency technique as an appropriate texture analysis tool. A defined correlation between texture changes and color differences was obtained. Furthermore, the whiteness of the papers clearly affected the final printed colors.

Print defects like banding from a digital press involve not only luminance variation, but also chrominance variation. As digital presses place one color separation at a time, the contrast and spatial pattern of the print defects are color-space dependent. Characterizing the color-dependent features of the banding signal enables us to simulate the banding on natural document images in a more accurate way that matches the characteristics of the banding generation mechanism within the digital press. A framework is described for color-dependent banding characterization including the following steps: printing and scanning uniform patches that sample colorant combinations throughout the input document sRGB color space, extracting banding signals in the CMYK color space of the target device, and modeling the banding features in a perceptually uniform color space. We obtain a full banding features LUT for every color point in the input sRGB space by interpolating banding features extracted from measured color points. The color-dependent banding simulation framework is developed based on the banding features LUT. Using the information contained in this LUT, a single banding prototype signal is modulated in a color-space-dependent fashion that varies spatially across the natural document image. Proper execution of the framework of banding characterization and simulation requires careful calibration of each system component, as well as implementation of a complete color management pipeline.

Digital halftoning provides a mechanism for rendering continuous-tone images on devices such as printers. With electrophotography, the deposition of toner within the area of a given printer addressable pixel is strongly influenced by the halftone values of the immediately neighboring pixels. To account for these effects, it is necessary to embed a printer model in the halftoning algorithm. In our previous work, we used an efficient strategy to account for the impact of a 5x5 neighborhood of pixels on the central pixel absorptance. Now we examine the potential influence of a much larger neighborhood (45x45) of the digital halftone image on the measured value of a printed pixel at the center of that neighborhood. The experiment shows that the extended model yields a significant improvement in the accuracy of the prediction of the pixel values of the printed and measured halftone image.

Periodic clustered-dot screens are widely used for electrophotographic printers due to their print stability. However, moir´e is a ubiquitous problem that arises in color printing due to the beating together of the clustered-dot, periodic halftone patterns that are used to represent different colorants. This beating or interference phenomenon introduces spurious low frequency (large period) patterns in the printed output that are very objectionable to the viewer. The traditional solution in the graphic arts and printing industry is to rotate identical square screens to angles that are maximally separated from each other. For example, the classic three-color screen set rotates three identical square screens to the angles 15°, 45°, and 75°, respectively. However, the effectiveness of this approach is limited when printing with more than four colorants, i.e. N-color printing, where N >4. Moreover, accurately achieving the angles that have maximum angular separation requires a very high resolution plate writer, as is used in commercial offset printing. In this paper, we propose a systematic way to design color screen sets for periodic, clustered-dot screens that offers more explicit control of the moir´e properties of the resulting screens when used in color printing. We find a general concept for moir´e-free screen design that is called lattice-based screen design. The basic concept behind our approach is the creation of the screen set on a 2-dimensional lattice in the frequency domain and then picking each fundamental frequency vector of the individual colorant planes in the created spectral lattice according to the desired properties. The halftone geometry of a screen set is the set of angles and frequencies in units of lines per inch (LPI) of each screen plane. The lattice-based screen design offers more flexibility in designing N-color screen sets with different halftone geometries, and all of them are guaranteed to be all-orders moir´e-free. For example, by creating a square lattice in the frequency domain, square N-color moir´e-free screen sets that consist of N rotated square screens can be achieved. The proposed approach maintains the advantage of square clustered-dot screen design and is based on low addressability of digital printing. We also propose several symmetry measures, and use them to compare the proposed 4-color square screen set and the screen sets based on a previous moir´e-free N-color non-orthogonal approach. The proposed screen set is shown to have better symmetry properties.

In order to increase density of colour and improve ink coverage when printing onto a range of non standard substrates, this paper will present research into multi-layering of colour and the appearance of colour at 'n' levels of ink coverage. Returning to our original investigation of artist's requirements when making inkjet prints, these observations are based on empirical approaches that address the need to present physical data that is more useful and meaningful to the designer. The study has used multi-pass printed colour charts to measure colour and to provide users with an understanding at a soft-preview level to demonstrate the appearance of printed colour on different substrates. Test results relating to the appearance of print on different surfaces, and a series of case studies will be presented using recent research into the capabilities of UV printing technology, which has widened the opportunities for the designer to print onto non-standard materials. It will also present a study into layering of greys and gloss in order to improve the appearance of printed images onto metal.

In this paper, we consider a dual-mode halftoning process for the electrophotographic laser printer - a low frequency halftoning for smooth regions and a high frequency halftoning for detail regions. These regions are described by an object map that is extracted from the page description language (PDL) version of the document. This manner of switching screens depending on the local content provides a stable halftone without artifacts in smooth areas and preserves detail rendering in detail or texture areas. However, when switching between halftones with two different frequencies, jaggies may occur along the boundaries between areas halftoned with low and high frequency screens. To reduce the jaggies, our screens obey a harmonic relationship. In addition, we implement a blending process based on a transition region. We propose a nonlinear blending process in which at each pixel, we choose the maximum of the two weighted halftones where the weights vary according to the position in the transition region. Moreover, we describe an on-line tone-mapping for the boundary blending process, based on an off-line calibration procedure that effectively assures the desired tone values within the transition region.

Common ink-saving techniques usually restrict the ink consumption when printing a document by replacing a percentage of cyan, magenta, and yellow, by black ink. Even though such methods achieve a considerable reduction in the amount of ink used in a page, the visual quality of the print is affected and unpleasing effects in pastels and skin tones are observed. On the other hand, the quality of the print is not only affected by the ink-saving algorithm, but also by the way the color halftoning algorithm arranges the dots in the print. Therefore, the relationship between the contents of the document to be printed and the printing process needs to be addressed by the ink-saving strategy. A color direct binary search halftoning method that strives to minimize both the ink usage and the perceived error between the continuous-tone color image and the color halftone image is proposed. Our goals are to estimate the effects of the ink-saving module of a printing workflow in individual regions of the document, and to determine the dot arrangement and ink combination that consumes the least amount of ink while preserving printing quality.

The present work investigates the transmission of light through stacks of halftone printed transparencies. We propose a spectral transmittance model describing the multiple reflections of light between the transparencies, whose individual reflectance and transmittance have themselves been obtained by a prediction model. The model for single printed transparency involves the multiple reflections of light between the interfaces as well as the orientation-dependent attenuations of light within the plastic and ink layers. A procedure enables converting the nominal ink surface coverages into effective ones by taking into account the spreading of the inks. Calibration of the model is based on printing a small number of color patches on one transparency and measuring their spectral transmittance. Regarding the stacks of transparencies, an experimental test carried out with inkjet printed samples shows good agreement between predictions and measurements for stacks of two, three and four transparencies. Stochastic halftones are used in order to avoid the apparition of moiré patterns when superposing the halftones. By inversion of the model, we are able to determine the halftone colors to print on each transparency in order to obtain by superposition one targeted color. An original application of this, called "color matching", consists in producing one color of stack from various combinations of colors on the transparencies. The prediction accuracy of the proposed model guarantees the good visual uniformity of the resulting colored area.

In this paper, we proposed an accurate estimation method for spectral reflectance of objects captured in an image. The spectral reflectance is simply modeled by a linear combination of three basic spectrums of R, G, and B colors respectively, named as spectral reflective bases of objects, which are acquired by solving a linear system based on the principle of color metamerism. Some experiments were performed to evaluate the accuracy of the estimated spectral reflectance of objects. The average mean square error of 24 colors in Macbeth checker between we simulated and the measured is 0.0866, and the maximum is 0.310. In addition, the average color difference of the 24 colors is less than 1.5 under the D65 illuminant. There are 13 colors having their color difference values less than 1, and other 8 colors having the values during the range of 1 and 2. Only three colors are relatively larger, with the differences of 2.558, 4.130 and 2.569, from the colors of No. 2, No. 13, and No. 18 in Macbeth checker respectively. Furthermore, the computational cost of this spectral estimation is very low and suitable for many practical applications in real time.

Projectors have become common display devices, not only for office and school presentations, but also for home theater entertainment. Although a completely dark room is the ideal venue for watching a projected image, in most situations (including classrooms and conference rooms) the viewing conditions are not completely dark, and ambient light falling on the screen produces a background light level with the image projected on top. As the background light increases, it becomes more difficult to see the projected image, which becomes dull and may appear washed out. What is really happening is that the ambient light reduces the contrast of the image. While the amount of light contributing to the image remains the same, more light has been projected onto the screen by other light sources. This effect can be reduced by employing the white-peaking function of a digital light-processing (DLP) projector, which adjusts the white segment of the color wheel, resulting in more natural and vivid images. Although the chromaticity coordinates for an image projected with and without white peaking are the same, when white is added to the projected image, the perceived hue changes. This phenomenon is known as the Abney effect. This paper presents a model of this hue-shift phenomenon and proposes a hue-correction method. For evaluation purposes, an observer-preference test is conducted on several test images with and without hue shifts, and z-scores are utilized to compare the results.

Number of pixels on mobile displays is rapidly increasing. Recently, mobile displays with more than one million pixels have been introduced into markets. However, most of multimedia contents to be displayed on mobile displays have much smaller pixel counts. For example, number of pixels for a T-DMB(terrestrial digital multimedia broadcasting) sequence is 320x240. When enlargement is applied to input sequence, perceived image quality would be degraded. Increase in visibility of block noise is one of the major reasons for image quality degradation on mobile displays. This paper presents a simple and computationally efficient method to reduce visibility of block noise on enlarged multimedia sequences. In proposed method, a simple low pass filtering is selectively applied to the pixels of block noises for reduction of block noise visibility as well as faithful reproduction of image details.

By researching the principle of colorimetric characterization method and Support Vector Regression (SVR), we analyze the feasibility of nonlinear transformation from scanner RGB color space to CIELAB color space based on SVR and built a new characterization model. Then we use the MATLABR2009a software to make a data simulation experiment to verify the accuracy of this model and figure out the color differences by CIEDE2000 color difference formula. Based on CIEDE2000 color difference formula, the average, the maximum and the minimum color differences of the training set are 1.2376, 2.5593 and 0.2182, the average, the maximum and the minimum color differences of the text set are 1.9318, 4.1421 and 0.4228. From the experimental results, we can make a conclusion that SVR can realize the nonlinear transformation from scanner RGB color space to CIELAB color space and the model satisfies the accuracy of scanner characterization. Therefore, SVR can be used into the color scanner characterization management.

In the color printing process, the thickness and uniformity of ink have a great affect on the color reproduction. The ink thickness uniformity is an important parameters of measuring the quality of printing. Based on the fluorescent additives may absorb ultraviolet light and exit blue light or visible light and by considering the expansion of the ink, optical properties of paper with fluorescent additives , the internal lateral spread of light in paper with fluorescent additives and the fluorescent Clapper-Yule spectral reflectance prediction model, we introduce two factor parameters which are the initial thickness of the inks and the factor of ink thickness variation. A model for deducing ink thickness variations of printing on the fluorescent substrate is developed by the least square method and the spectrum reflectance of prints which measures the ink thickness variations. The correctness of the conclusions are verified by experiment.

Saving of toner/ink consumption is an important task in modern printing devices. It has a positive ecological and social impact. We propose technique for converting print-job pictures to a recognizable and pleasant color sketches. Drawing a "pencil sketch" from a photo relates to a special area in image processing and computer graphics - non-photorealistic rendering. We describe a new approach for automatic sketch generation which allows to create well-recognizable sketches and to preserve partly colors of the initial picture. Our sketches contain significantly less color dots then initial images and this helps to save toner/ink. Our bio-inspired approach is based on sophisticated edge detection technique for a mask creation and multiplication of source image with increased contrast by this mask. To construct the mask we use DoG edge detection, which is a result of blending of initial image with its blurred copy through the alpha-channel, which is created from Saliency Map according to Pre-attentive Human Vision model. Measurement of percentage of saved toner and user study proves effectiveness of proposed technique for toner saving in eco-friendly printing mode.

In the color reproduction process, accurately predicting the color of recto-verso images and establishing a spectral reflectance model for halftones images are the great concern project of imaging quality control field. The scattering of light within paper and the ink penetration in the substrate are the key factors, which affect the color reproduction. A reflectance model for recto-verso color halftone prints is introduced in this paper which considers these factors. The paper based on the assumption that the colorant is non-scattering and the assumption that the paper is strong scattering substrate. By the multiple internal reflection between the paper substrate and the print-air interface of light, and the light along oblique path of the Williams-Clapper model, we proposed the color spectral reflectance precise prediction model of recto-verso halftone images. In the study, we propose this model for taking into account ink spreading, a phenomenon that occurs when printing an ink halftone in superposition with one or several solid inks. The ink-spreading model includes nominal-to-effective dot area coverage functions for each of the different ink overprint conditions by the least square curve fitting method, so the functions for physical dot gain of various overprint halftones are given. This model provided a theoretical foundation for color prediction analysis of recto-verso halftone images and the development of image quality detection system.

Based on the feature of the second-order FM halftone dots and the interaction feature among ink, paper and air, a spectral prediction model for the second-order FM halftone prints for the spectral Neugebauer random mixing model and dot-on-dot mixing model is developed by using a weighting factor to signify the correlation proportion of two models. The new spectral prediction model also includes the Yule-Nielsen effect by taking into account ink spreading in all ink superposition conditions. We create an ink spreading function for each superposition condition to indicate the difference of ink spreading for ink dots printing on different superposition, which maps nominal to effective dot surface coverage. Our results shown that in the ink jet printing, the mean and max ΔE difference between measured and predicted values are 2.90 and 7.26, smaller than the difference predicted by the model that is not taken into account ink spreading, which are 5.52 and 12.81. The prediction accuracy is considerably improved by the new model.

Multidimensional lookup tables (LUTs) are often used to describe the response of physical systems to multiple inputs. However these tables are also tensors, and in this paper we will use tensor decomposition to greatly reduce the number of parameters needed to generate an accurate approximation to the tensor, and discuss how to determine these parameters from a small number of known tensor elements. We will use this approach to generate printer models, which are CMY or CMYK to L*a*b* LUTs where each element is an L*a*b* value for one CMYK formulation. The approach generates accurate results with a reasonable number of L*a*b* measurements, and can be used when nothing else is known about the system. It also runs much faster than the physics based models that are sometimes available for these systems.

Colony anaysis is used in a large number of engineerings such as food, dairy, beverages, hygiene, environmental monitoring, water, toxicology, sterility testing. In order to reduce laboring and increase analysis acuracy, many researchers and developers have made efforts for image analysis systems. The main problems in the systems are image acquisition, image segmentation and image analysis. In this paper, to acquire colony images with good quality, an illumination box was constructed. In the box, the distances between lights and dishe, camra lens and lights, and camera lens and dishe are adjusted optimally. In image segmentation, It is based on a genetic approach that allow one to consider the segmentation problem as a global optimization,. After image pre-processing and image segmentation, the colony analyses are perfomed. The colony image analysis consists of (1) basic colony parameter measurements; (2) colony size analysis; (3) colony shape analysis; and (4) colony surface measurements. All the above visual colony parameters can be selected and combined together, used to make a new engineeing parameters. The colony analysis can be applied into different applications.

Edge detection in grey scale image processing is a traditional research subject, but recently more and more researchers make efforts on the edge detection in color images. This paper presents a novel edge detection algorithm using the local, nonparametric estimation of the color image density. The method firstly analyses the edge shape information provided by the local probability distribution of the color image both in the horizontal and vertical directions respectively, then it obtains the modulus for the edge detection in the color image. With the increasing of window size, the other types of distributions can be simplified to the three types of the distributions presented in this study. In experiements, eleven different edge detection algorithms are compared for the three types of color images: smooth surface objects with a few edges; thin (or lines and curves) objects with many edges; and rough surface objects with more edges. And the algorithms include fractional, the first and the second order differential operators and other non-differential ones. Experiments show that the studied method is efficient.for edge extracting in a color image, and can give a satisfactory edge detection result in most cases.

When ink jet printers' drop size change, based on Clapper-Yule model, study reflectance prediction model for variable dot-size ink jet presswoke. At first, this article introduce variable drop size and the FM screening form of Clapper-Yule model; then, using the change of ink film thickness and FM screening dot, which are caused by drop change, extended Clapper-Yule model; at last, established the Clapper-Yule model which is extended by drop size, in addition, validated the advantage of the model by simulation.