This PDF file contains the front matter associated with SPIE-IS&T Proceedings Volume 6807, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and the Conference Committee listing.

The spectrum locus of a CIE chromaticity diagram defines the boundary within which all physically realizable color stimuli must fall. While that is a physical and mathematical reality that cannot be violated, it is possible to create colors that appear as if they were produced by physically impossible stimuli. This can be accomplished through careful control of the viewing conditions and states of adaptation. This paper highlights the importance of considering color appearance issues in the design of displays and specification of color gamuts and illustrates how the perceived color gamut can be manipulated significantly through the relationship between white-point and primary luminance levels without changing the chromaticity gamut of a display system. Using a color appearance model, such as CIECAM02, display color gamuts can be specified in perceptual terms such as lightness, chroma, brightness, and colorfulness rather than in strictly physical terms of the stimuli that create these perceptions. Examination of these perceptual gamuts, and their relationships to the viewing conditions, allows demonstration of the possibility of producing display gamuts that appear to reach beyond the locus of pure spectral colors when compared with typical display setups.

Rods act as color receptors in dim illumination. Several recent studies have measured the range of colors at low-light levels in different illuminants. This paper reviews these results and adds new experiments using long-wave-rich illumination, appropriate for rod and long-wave cone interactions. The experiment illuminates Munsell ColorChecker papers with 546, and then with 455 nm narrowband lights at radiances below cone thresholds. The third illuminant is 625 nm light, above cone threshold. Observers make asymmetric matches of the ColorChecker using a digital computer display. The observers make these matches while viewing the entire ColorChecker. Observers report a wide range of colors from the combination of cone response to 625 nm plus rod response to 546 nm light. The same is true with the combination of cone response to 625 nm plus rod response to 455 nm light. Although the color matches vary with the ColorChecker's reflectances, the range of colors is the same. Since these experiments use illuminants more appropriate for rod-cone interactions, they measure a much greater color gamut than photopic illuminants. They also provide new data that clarifies how the rod information interacts with the cone-cone color channels. Color appearances indicate rods share M- and S-color channels.

Capturing natural scenes with high dynamic range content using conventional RGB cameras generally results in saturated and underexposed and therefore compromising image areas. Furthermore the image lacks color accuracy due to a systematic color error of the RGB color filters. The problem of the limited dynamic range of the camera has been addressed by high dynamic range imaging^{1, 2} (HDRI): Several RGB images of different exposures are combined into one image with greater dynamic range. Color accuracy on the other hand can be greatly improved using multispectral cameras,³ which more accurately sample the electromagnetic spectrum. We present a promising combination of both technologies, a high dynamic range multispectral camera featuring a higher color accuracy, an improved signal to noise ratio and greater dynamic range compared to a similar low dynamic range camera.

Generally, to acquire an HDR image, many images that cover the entire dynamic range of the scene with different exposure times are required, then these images are fused into one HDR image. This paper proposes an efficient method for the HDR image acquisition with small number of images. First, we estimated scenic dynamic range using two images with different exposure times. These two images contain the upper and lower limit of the scenic dynamic range. Independently of the scene, according to varied exposure times, similar characteristics for both the maximum gray levels in images that include the upper limit and the minimum gray levels in images that include the lower limit are identified. After modeling these characteristics, the scenic dynamic range is estimated using the modeling results. This estimated scenic dynamic range is then used to select the proper exposure times for the acquisition of an HDR image. We selected only three proper exposure times because entire dynamic range of the cameras could be covered by three dynamic range of the cameras with different exposure times. To evaluate the error of the HDR image, experiments using virtual digital camera images were carried out. For several test images, the error of the HDR image using proposed method was comparable to that of the HDR image which utilize more than ten images for the HDR image acquisition.

Two methods are described to accurately estimate diffuse and specular reflectance parameters for colors, gloss intensity and surface roughness, over the dynamic range of the camera used to capture input images. Neither method needs to segment color areas on an image, or to reconstruct a high dynamic range (HDR) image. The second method improves on the first, bypassing the requirement for specific separation of diffuse and specular reflection components. For the latter method, diffuse and specular reflectance parameters are estimated separately, using the least squares method. Reflection values are initially assumed to be diffuse-only reflection components, and are subjected to the least squares method to estimate diffuse reflectance parameters. Specular reflection components, obtained by subtracting the computed diffuse reflection components from reflection values, are then subjected to a logarithmically transformed equation of the Torrance-Sparrow reflection model, and specular reflectance parameters for gloss intensity and surface roughness are finally estimated using the least squares method. Experiments were carried out using both methods, with simulation data at different saturation levels, generated according to the Lambert and Torrance-Sparrow reflection models, and the second method, with spectral images captured by an imaging spectrograph and a moving light source. Our results show that the second method can estimate the diffuse and specular reflectance parameters for colors, gloss intensity and surface roughness more accurately and faster than the first one, so that colors and gloss can be reproduced more efficiently for HDR imaging.

A major challenge to convert non-printers into customers who order tangible products has, up till now, been the image selection process. Implementing functionality to ease the usage of software for organizing, archiving, displaying and also for ordering has become paramount as it frees the user, enabling him/her to have fun and get creative with his images both now, and more importantly, also in the future. In this paper we present approaches to exploit photo metadata and metadata from photo management tools for the selection process and show their integration into a special-purpose order software and also in combination with publicly available software.

Large-scale, direct view TV screens, in particular those based on liquid crystal technology, are beginning to use subpixel structures with more than three subpixels to implement a multi-primary display with up to six primaries. Since their input color space is likely to remain tri-stimulus RGB we first focus on some fundamental constraints. Among them, we elaborate simplified gamut mapping architectures as well as color filter geometry, transparency, and chromaticity coordinates in color space. Based on a 'display centric' RGB color space tetrahedrization combined with linear interpolation we describe a simulation framework which enables optimization for up to 7 primaries. We evaluated the performance through mapping the multi-primary design back onto a RGB LC display gamut without building a prototype multi-primary display. As long as we kept the RGB equivalent output signal within the display gamut we could analyze all desirable multi-primary configurations with regard to colorimetric variance and visually perceived quality. Not only does our simulation tool enable us to verify a novel concept it also demonstrates how carefully one needs to design a multiprimary display for LCD TV applications.

Displays are coming on the market that can produce a larger range of colors over EBU and this has led to much research on the topic of how to use the additional color gamut volume provided by the displays. Some research has focused on different methods to map colors from small to large gamuts, whereas this paper focuses on defining the required gamut boundaries for natural content. Two gamuts were created from the results of a psychophysical experiment that asked observers to choose their preferred image in terms of saturation. One gamut corresponded to the median value of their choices and the second gamut corresponded to the 90% value of their choices. The results indicated that even at the 90% value, the resulting gamut was smaller than that of the wide-gamut display for most hues and actually closer to EBU for some hues. These results are display independent, at least when considering modern displays that can reach luminance values above 250cd/m².

We have defined an inverse model for colorimetric characterization of additive displays. It is based on an optimized three-dimensional tetrahedral structure. In order to minimize the number of measurements, the structure is defined using a forward characterization model. Defining a regular grid in the device-dependent destination color space leads to heterogeneous interpolation errors in the device-independent source color space. The parameters of the function used to define the grid are optimized using a globalized Nelder-Mead simplex downhill algorithm. Several cost functions are tested on several devices. We have performed experiments with a forward model which assumes variation in chromaticities (PLVC), based on one-dimensional interpolations for each primary ramp along X, Y and Z (3×3×1-D). Results on 4 devices (2 LCD and a DLP projection devices, one LCD monitor) are shown and discussed.

Field sequential color (FSC) LCD is one of the preferred display technologies to achieve wide color gamut and high luminous efficiency. But this technology suffers from an unpleasing color breakup effect. This phenomenon can be reduced by adding a white primary. As RGBW primaries are recommended for FSC-LCD, the next question is how to convert standard RGB signals to RGBW without large color variations. The present study first optimal the spectra of RGB primaries using the 3D gamut boundaries of standard object color spectra (SOCS) database and Adobe RGB in CIECAM02 space with observer metamerism constraint. The optimal RGB primaries then were used to derive six modes for RGB to RGBW conversion. The final step is to further optimize color correction matrix based on CIE170-1:2006 'age and size dependent cone fundamentals' to compensate the visual color shift of elders.

Color image coding for d-cinema is explored using luminance contour plots of a few standards, a laser-based projection system, and a film stock. The luminance contour plots are in u'v' space. Several color image coding representations are surveyed. And a color image coding system is suggested for efficient perceptual color difference encoding.

Nowadays, the visual information is widely used for several applications such as medical diagnosis, video-surveillance... This information needs to be displayed in order to exploit the contained data. So, the display devices market is growing very quickly and the used technologies are different from a manufacturer to another. This leads to a need of a comparison between displays of different technologies but also ones from the same technology. In this paper, we describe two methodologies that we have used, for a subjective cross-media evaluation and a single media evaluation, in the context of image quality for display reproduction. We compare the results obtained by the two methodologies in order to determine if it is possible to replace a cross-media evaluation by a single media evaluation. We describe how we have used, the characterization of a display in order to simulate a display color reproduction on another one. We explain the different statistical non-parametric tests that we have used, to analyze the results. And we discuss about the results obtained for the two cases, and the possibility to replace a cross-media evaluation by a single-media evaluation.

In this paper a model for the LCD moving image representation is presented. It is combined with a human visual system perception model to analyze the influence a display has on the perceived image quality. Two main fields of moving image representation are discussed: The spatial properties of a display, namely the pixel shape or spatial aperture, and the temporal properties of a display given by the display response or temporal aperture. Both properties affect the image quality: The LCD pixel shape leads to a higher sharpness impression but also to an enhancement of errors such as block noise. The temporal LCD hold-type behavior combined with the slow response of the liquid crystal lead to a motion blur in moving objects. Both effects are explained numerically and analytically and demonstrated with simulation results.

With the current trend of digital convergence in mobile phones, mobile manufacturers are researching how to develop a mobile beam-projector to cope with the limitations of a small screen size and to offer a better feeling of movement while watching movies or satellite broadcasting. However, mobile beam-projectors may project an image on arbitrary surfaces, such as a colored wall and paper, not on a white screen mainly used in an office environment. Thus, color correction method for the projected image is proposed to achieve good image quality irrespective of the surface colors. Initially, luminance values of original image transformed into the YCbCr space are changed to compensate for spatially nonuniform luminance distribution of arbitrary surface, depending on the pixel values of surface image captured by mobile camera. Next, the chromaticity values for each surface and white-screen image are calculated using the ratio of the sum of three RGB values to one another. Then their chromaticity ratios are multiplied by converted original image through an inverse YCbCr matrix to reduce an influence of modulating the appearance of projected image due to spatially different reflectance on the surface. By projecting corrected original image on a texture pattern or single color surface, the image quality of projected image can be improved more, as well as that of projected image on white screen.

The standard color space conversion equations usually do not explicitly account for a change in luminance. In an effort to understand color space conversion better, the color space conversion equations are derived from first principles. The solution shows how to calculate the RGB scale factors using xyY measured at a RGB triplet that is not restricted to white. Also, the color space conversion equations are discussed in the context of color encoding topics including gamma, luminance, and negative primary settings.

An LCD Driver with on-chip frame buffer and 3 times image compression codec reaching visually lossless image quality is presented. The frame buffer compression codec can encode and decode up to eight pixels in one clock cycle. Integrating a whole frame buffer with RGB=888 bits into the display driver sharply reduces power dissipated between the IO pad and PCB board at a cost of 50% IC die area increase. The existing working chip (STE2102, a ram-less LCD Driver with die size of 170mm x 12mm) is manufactured by ST Micro 0.18μm high voltage CMOS process. A new chip design with on-chip frame buffer SRAM and 3 times compression codec supporting QVGA (320x240) is completed which reduces the frame buffer SRAM density and area by a factor of ~3.0 times and cuts the power consumption of the on-chip SRAM frame buffer by ~9.0 times of which 3 times is contributed by less capacitive bit line load and another 3 times from data rate reduction from image compression. The compression codec having 25K gates in encoder and 10K in decoder accepts both YUV and RGB color formats. An on-chip color-space-conversion unit converts the decompressed YUV components with 420, 422 and 444 formats to be RGB format before driving out to be displayed. The high image quality is achieved by applying some patented proprietary compression algorithms including accurate prediction in DPCM, a Golomb-Rice like VLC coding with accurate predictive divider and an intelligent bit rate distribution control.

Metrics are proposed which allow the evaluation of the intrinsic smoothness of an output colour transform. One metric is based on taking the second derivative of the transform. The second method computes a series of smooth gradients and evaluates the differences between these gradients and the actual output values. A psychophysical experiment was performed to evaluate the proposed metrics, and both were found to be highly correlated with the observers' visual scale values.

A watermark is embedded into a color image. The relationship between embedding and compression process is investigated. The compression ratio (CR) is adjusted from 2 to 15, and three gray-levels of the original image are changed, their average gray-levels are individually 126, 161 and 196. From the experimental results, there is an apparent inclination about higher gray-level makes higher PSNR. There are two kinds of compression methods in the compression process, one includes color space transform and sampling, and this method has higher CR, the other has not these steps and it has lower CR. In this paper the relationship of these parameters such as the gray-level of the image, the parameters of frequency domain are also discussed and analyzed. The relation between color saturation and normalized correlation (NC) ratio has been quantitatively analyzed, it is found that the extracted watermark has the best quality when the saturation factor is set to the value of 0.2, and the NC value is lower when the processing has lower color factor. The curve of NC drops gradually when the color factor is over 0.4. The main reason of this result is also discussed in the final discussion. In our proposed approach, a systematic analysis is performed. The adaptive methods are selected to obtain the optimum conditions to embed the watermark into an image.

Substrates found in standard digital color printing applications frequently contain optical brightening agents (OBAs). These agents fluoresce under near UV light and are predominantly intended to increase the perceived paper white and thus create a paper look and feel which is preferred by customers. The fluorescence phenomenon poses a considerable challenge in standard color management applications, however, the problem description can be inverted and information can be embedded in a printed color image that is perceptually invisible under normal illumination, but revealed via substrate fluorescence under UV illumination. From a practical standpoint, the approach works with standard high brightness office-type papers and does not require any special materials or media, or any modifications to the imaging path inside the machine. This means that certain security aspects can now produced in an essentially cost-neutral way[1].

Museums hold a wide variety of cultural properties and they organize exhibitions for the public. In history museums, a number of interpretive materials are necessary to present a specific historical theme. However, due to limitation of space, the number of displayed materials is severely restricted. There are various types of guidance systems in museums, however, most systems have not yet responded to visitors' needs. Therefore, a useful guidance system is necessary to satisfy their needs and also to enhance their understandings of the exhibitions. In order to create such guidance system, applications of imaging technology can become a solution to overcome these restrictions and meet the requirements. In this research, a visual guidance system using a data projector was examined in the National Museum of Japanese History. In the kimono (traditional Japanese clothing) section, the projector was used to simulate color changes of the materials under different illuminants. The projector also highlighted areas where annotations were featured in the kimono. The validity of using the projector system was confirmed by results from an interview survey. To further develop this visual guidance system, an augmented reality system consisted of cooperation between the projector and a digital camera was also examined.

This paper describes a method for measurement and analysis of surface reflection properties of oil paints under a variety of conditions. First, the radiance factor of a painting surface is measured at different incidence and viewing angles by using a gonio-spectro photometer. The samples are made from different oil paint materials on supporting boards with different paint thicknesses. Next, typical reflection models are examined for describing 3D reflection of the oil painting surfaces. The models are fitted to the observed radiance factors from the oil paint samples. The Cook- Torrance model describes well the reflection properties. The model parameters are estimated from the least-squared fitting to the genio-photometric measurements. Third, the reflection properties are analyzed on the basis of several material conditions such as pigment, supporting material, oil quantity, paint thickness, and support color.

This presentation will describe artists, practitioners and scientists, who were interested in developing a deeper psychological, emotional and practical understanding of the human visual system who were working with wavelength, paint and other materials. From a selection of prints at The Prints and Drawings Department at Tate London, the presentation will refer to artists who were motivated by issues relating to how colour pigment was mixed and printed, to interrogate and explain colour perception and colour science, and in art, how artists have used colour to challenge the viewer and how a viewer might describe their experience of colour. The title Colour in Flux refers, not only to the perceptual effect of the juxtaposition of one colour pigment with another, but also to the changes and challenges for the print industry. In the light of screenprinted examples from the 60s and 70s, the presentation will discuss 21^st century ideas on colour and how these notions have informed the Centre for Fine Print Research's (CFPR) practical research in colour printing. The latter part of this presentation will discuss the implications for the need to change methods in mixing inks that moves away from existing colour spaces, from non intuitive colour mixing to bespoke ink sets, colour mixing approaches and colour mixing methods that are not reliant on RGB or CMYK.

The objective of this project is to establish a practical application of the concept of Color Universal Design (CUD), the design that is recognizable to all color vision types. In our research, we looked for a clearly distinguishable combination of hues of four colors - black, red, green, and blue - which are frequently used in these circumstances. Red-green confusion people do not confuse all kinds of red and all kinds of green. By selecting particular hues for each color, the ability to distinguish between the four colors should be greatly improved. Our study thus concluded that, by carefully selecting hues within the range of each color category, it is possible to establish color-combinations which are easily distinguishable to people of all color-vision types in order to facilitate visual communication.

In principle, an artificial retina should mimic as much as possible the spectral sensitivities of the real retina. For technological reasons, building such an artificial device can lead to spectral approximations in comparison with the real sensitivities. To understand if possible discrepancies can determine big differences in the final perception, the whole visual system should be taken into consideration, not only the retinal input signal difference. This paper aims at investigate how retinal sensitivity differences should affect the final perception. However, answering to this question is a very complex problem related to the whole visual system, that we do not want to extensively address in this paper. We only want to investigate the relationship between the spatial aspects of color perception and the spectral differences among cone sensitivities. Moreover, a personal interdifference has been observed in cone spatial distribution between human subjects, without any corresponding significant difference in final color sensation. It is likely that spatial compensation, performed by human observers, strongly decreases this subjectivity in color signal. We aim at address if a similar principle should be considered in artificial vision. In this paper we analyze the interdifference among integrated values obtained using different organic-based artificial sensors with different spectral sensitivities. Experiments show a significant decrease of the effect of spectral sensitivity sensor differences when a spatial color correction is applied.

Digital cameras are widely used in many applications, such as digital still cameras, camcorders, camera phones, and video surveillance. Advances in large resolution CCD/CMOS sensors coupled with the availability of low-power image signal processors have led to the development of digital cameras with both high resolution image and short visual clip capabilities. The red, green, or blue color values obtained from a camera sensor are device-dependent. Thus there is a need to characterize these values in a device-independent fashion and provide a color correction. For simplicity, common methods presume a linear transformation to perform the color conversion. The problem translates to finding the transformation matrix and the offset vector. One well known approach uses a white-preserving constraint in the optimization. This approach requires that source data and reference data have the same exposure values. However, source data and reference data usually have different exposure values, and exposure information is either unavailable or inaccurate. We propose a new method that provides color conversion by linear transformation optimization with gray preservation. Our method allows for differing exposures between images from the target sensor and the color reference. Experiments show that images resulted from our method look more colorful than those from previous methods.

Many consumer digital color cameras have a single image sensor with a color filter array. The data captured by the single image sensor are called raw data. An effective compression of the raw data is highly demanded. This paper proposes a raw data compression method using existing image coding framework. The proposed coding method is performed to minimize error between the observed raw data and the decoded raw data. Experimental comparisons demonstrate that the proposed method has high performance compared to existing methods.

Closed loop color calibration is a process to maintain consistent color reproduction for color printers. To perform closed loop color calibration, a pre-designed color target should be printed, and automatically measured by a color measuring instrument. A low cost sensor has been embedded to the printer to perform the color measurement. A series of sensor calibration and color conversion methods have been developed. The purpose is to get accurate colorimetric measurement from the data measured by the low cost sensor. In order to get high accuracy colorimetric measurement, we need carefully calibrate the sensor, and minimize all possible errors during the color conversion. After comparing several classical color conversion methods, a regression based color conversion method has been selected. The regression is a powerful method to estimate the color conversion functions. But the main difficulty to use this method is to find an appropriate function to describe the relationship between the input and the output data. In this paper, we propose to use 1D pre-linearization tables to improve the linearity between the input sensor measuring data and the output colorimetric data. Using this method, we can increase the accuracy of the regression method, so as to improve the accuracy of the color conversion.

In many cases, rendering images using color management approach may result in unsatisfactory color, particularly for cases when the gamut mismatch is large and the source / destination profile pair does not lead to a satisfactory color. This more often the case when images on laptop computer screens with limited color gamut are transferred to print and color management is used. For those cases, we present a method of improving image quality by manipulating the display profile such that the color quality of the printouts is not compromised by the small gamut of the portable display and color management. The basic idea consists of using in the color management pipeline of a virtual gamut that has the role of either the source or of the destination depending on the type of transformation and the gamut size of the source and destination in the color management pipeline. In case the mismatch between the source and destination gamut is under a threshold the virtual gamut is not used. This virtual gamut is constructed directly in the CIE 1931 chromaticity diagram, although other color spaces may be used. A procedure to derive a constant hue line from two adjacent lines is presented. The chromaticities of the virtual gamut are computed based on the replaced gamut chromaticities and a weighting factor computed automatically at the time of rendering. The method proves to give very pleasing results in prints for example and the boost in saturation approximates very well the color enhancement achieved in silver halide photographic prints even for relatively modest print media.

Sharpness is an important attribute that contributes to the overall impression of printed photo quality. Often it is impossible to estimate sharpness prior to printing. Sometimes it is a complex task for a consumer to obtain accurate sharpening results by editing a photo on a computer. The novel method of adaptive sharpening aimed for photo printers is proposed. Our approach includes 3 key techniques: sharpness level estimation, local tone mapping and boosting of local contrast. Non-reference automatic sharpness level estimation is based on analysis of variations of edges histograms, where edges are produced by high-pass filters with various kernel sizes, array of integrals of logarithm of edges histograms characterizes photo sharpness, machine learning is applied to choose optimal parameters for given printing size and resolution. Local tone mapping with ordering is applied to decrease edge transition slope length without noticeable artifacts and with some noise suppression. Unsharp mask via bilateral filter is applied for boosting of local contrast. This stage does not produce strong halo artifact which is typical for the traditional unsharp mask filter. The quality of proposed approach is evaluated by surveying observer's opinions. According to obtained replies the proposed method enhances the majority of photos.

It has been well known since the earliest days of color photography that color-balance in general, and facial reproduction (flesh tones) in particular, are of dominant interest to the consumer, and significant research resources have been expended in satisfying this need. The general problem is a difficult one, spanning the factors that govern perception and personal preference, the physics and chemistry of color reproduction, as well as wide field of color measurement specification, and analysis. However, with the advent of digital photography and its widespread acceptance in the consumer market, and with the possibility of a much greater degree of individual control over color reproduction, the field is taking on a new consumer-driven impetus, and the provision of user facilities for preferred color choice now constitutes an intense field of research. In addition, due to the conveniences of digital technology, the collection of large data bases and statistics relating to individual color preferences have now become a relatively straightforward operation. Using a consumer preference approach of this type, we have developed a user-friendly facility whereby unskilled consumers may manipulate the color of their personal digital images according to their preferred choice. By virtue of its ease of operation and the real-time nature of the color-correction transforms, this facility can readily be inserted anywhere a consumer interacts with a digital image, from camera, printer, or scanner, to web or photo-kiosk. Here the underlying scientific principles are explored in detail, and these are related to the practical color-preference outcomes. Examples are given of the application to the correction of images with unsatisfactory color balance, and especially to flesh tones and faces, and the nature of the consumer controls and their corresponding image transformations are explored.

The red eye artifacts are troublesome defect of amateur photos. Correction of red eyes during printing without user intervention and making photos more pleasant for an observer are important tasks. The novel efficient technique of automatic correction of red eyes aimed for photo printers is proposed. This algorithm is independent from face orientation and capable to detect paired red eyes as well as single red eyes. The approach is based on application of 3D tables with typicalness levels for red eyes and human skin tones and directional edge detection filters for processing of redness image. Machine learning is applied for feature selection. For classification of red eye regions a cascade of classifiers including Gentle AdaBoost committee from Classification and Regression Trees (CART) is applied. Retouching stage includes desaturation, darkening and blending with initial image. Several versions of approach implementation using trade-off between detection and correction quality, processing time, memory volume are possible. The numeric quality criterion of automatic red eye correction is proposed. This quality metric is constructed by applying Analytic Hierarchy Process (AHP) for consumer opinions about correction outcomes. Proposed numeric metric helped to choose algorithm parameters via optimization procedure. Experimental results demonstrate high accuracy and efficiency of the proposed algorithm in comparison with existing solutions.

Copier color mapping is the color modeling and mapping from the scanner RGB color space to the printer device color space. It may be aimed for exact/closest color matching or for preference color matching from the source hardcopy to the reproduced hardcopy. It is not simply the linking of a scanner color characterization and a printer color characterization. Unlike other cross-color reproduction systems in which both the source color space and the destination color space are well-defined, copy source types are not controllable in general; thus, the source color space (e.g. the black and white points, color gamut, and the scanner response to the source) cannot be well-defined. Thus no exact color characterization can be made for general copy. A trade-off for the balance of overall copy reproduction or a fuzzy characterization is important for the color characterization. In this paper, we present a method for scanner characterization preserving the neutral balance, a method to characterize scanners with controllable extrapolation, selecting a gamut mapping method for optimized system color reproduction, and overall characterization methods for different source types and different print modes for the trade-off for overall copy color reproduction is achieved.

Color printer calibration is always performed in the presence of noise. A major part of this noise is due to the spatial non-uniformity of the printer. In many cases, the spatial non-uniformity does not repeat the same pattern page by page. Some calibration techniques use randomizing the locations of patches and averaging a large numbers of measurements to reduce the noise. Since the non-uniformity is a kind of systematic errors, it should be estimated and corrected in a more effective way. This presentation describes a method to provide a more accurate color calibration/characterization result by estimating the spatial non-uniformity presented on the printed target page and applying a correction to the very same page itself. Instead of defining the noise in the color measurement space, e.g. the CIE Lab space, the new method specifies the noise in the printer-dependent color space, e.g. the CMY space. After the first-round color calibration, an inverse transform, from CIE Lab to CMY, is derived from measurements of the entire printed target. The noise dC, dM, or dY is determined as the difference between the original CMY values and the output of the inverse transform with the measured Lab values as the transform input. Since color patch locations are stochastically arranged, any "noticeable" spatial pattern of the noise is most likely due to the printer non-uniformity in the corresponding channel. The nonuniformity can be estimated by spatially smoothing the noise terms and the result can be subtracted from the original CMY input for a second-round calibration to achieve higher color accuracy.

In this paper we present a method to characterize the printer color output with few samples. Color measurements previously obtained on other substrates and stored in the printer are used to increase the accuracy of measurements in a new target media, thus reducing the number of samples needed. The method is simple and generic; a geometrical warp is applied to the color space to adapt the differences between the two media. The warping is built with a small set of measurements on the target media and extended to the entire color space with bi-harmonic spline interpolation. We tested the method on a HP T1100 ink-jet printer, at different levels of sampling -from 27 to 512 points- and with seven different substrate families covering a wide variety of applications. For 125 samples, results show a mean estimation error across media of mean 0.67 dE76 and 95 percentile 1.48 dE76 with respect to the finer sampling of 512 samples. This represents an improvement in color accuracy with respect to linear interpolation of about 60%, a relationship holds at other levels of sampling. In conclusion, color space warping is proven to be an effective method to reduce the needed color samples by using previously characterized media.

Printing with white ink plays an important role in many printing processes, but white is difficult to integrate into colour management processes since conventional measurements are uncorrelated with the ink amount. A control method for white ink is proposed in which white is printed and measured over black. The resulting colorimetric densities can be modelled by polynomial regression, allowing accurate prediction of tonal value. The model can readily be inverted to predict the colorant amount required to match a given colorimetric density, and hence is a suitable method of measurement that can support process control and colour management.

In order to save time and money, more and more printing organizations are investing in on-line customer portals to allow uploading content and giving formal approvals based on soft proofs before the final production process (plate making and printing) can be initiated. The approvals are typically made on soft proofs of pages whereas, obviously, the images used for plate making are so-called imposed flats (a combination of pages rotated in such a way that the printed matter can be obtained after folding and cutting). The main goal of a soft proof of a page is to simulate accurately on a display device how the page will be finally printed. The quality expectations of a soft proof are very high since a formal approval implies contractual obligations from the printing organization. This quality, however, can be influenced by many parameters. By definition, soft proofs will be displayed on a monitor (being a light emitting device), whereas a print on paper can only be seen as the reflection of a light source. As a consequence, monitors can be described by an additive color model whereas printers or presses will be modeled by a subtractive color model. Other differences relate to how the image is generated: presses can only output binary information (ink or no ink) and continuous tones are simulated by using screening techniques whereas, on a monitor, a multi-level signal can generate different shades of a specific color. The differences described above are addressed by many color management systems available on the market today. An upcoming requirement in this area is that people do not only expect the color management software to behave well but also expect this software to validate its behavior. Another range of problems with soft proofs relates to the rendering (converting vector-based page data into bitmaps) and separation process. These can be divided in two classes: spatial issues (related to resolution differences, high-frequency patterns, aliasing problems etc.) and issues related to object layering (overprint and transparency issues). Also when optimizations are carried out for plate reuse across versioned products, many things can go wrong. In this paper, we will categorize the different potential problems occurring with soft proofs and examine in detail how these problems can be avoided. It will turn out that this can only be realized if one knows the details on how the printing plates will be generated in prepress production.

A novel method for resolution enhancement of Electro Photographic (EP) printers is presented. The proposed method is applicable for laser printers that have a partial-pixel exposure capability such as Pulse Width Modulation (PWM). By coupling partial exposure with anti-aliasing rendering, the proposed technology enables practically continuous addressability, namely, placement resolution. Using this technology we can show significant print quality improvement, such as the ability to render lines with arbitrary width and location. This would allow printing smooth line art at any angle with a relatively coarse pixel grid. The proposed method will thus provide better print quality compared to post process type resolution enhancement alternatives used today. The method has been tested theoretically using a Liquid EP (LEP) model, and experimentally confirmed.

Visual experiments, attesting visual preference, visual ranking and visual differentiation, are very important to academia and industry. They are traditionally performed into laboratories under controlled viewing conditions, resulting very costly in their execution, due to the time and effort involved by all participants. If controlled tests could be substituted by uncontrolled tests, a potential serious improvement could be obtained by eliminating a large part of the cost. In this work we investigate if, and to what extent, visual experiments performed under controlled viewing conditions can be substituted by uncontrolled experiments. A task of visual preference of prints is carried out. This task is performed in the laboratory, under controlled viewing conditions, and in many different places, under natural, artificial and mixed light. We observe statistical equivalence for preferences expressed in controlled or uncontrolled conditions that supports the hypothesis that visual preference can be assessed with uncontrolled tests.

Inherent to most multi-color printing systems is the inability to achieve perfect registration between the primary separations. Because of this, dot-on-dot or dot-off-dot halftone screen sets are generally not used, due to the significant color shift observed in the presence of even the slightest misregistration. Much previous work has focused on characterizing these effects, and it is well known that dot-off-dot printed patterns result in a higher chroma (C*) relative to dot-on-dot. Rotated dot sets are used instead for these systems, as they exhibit a much greater robustness against misregistration. In this paper, we make the crucial observation that while previous work has used color shifts caused by misregistration to design robust screens, we can infact exploit these color shifts to obtain estimates of misregistration. In particular, we go on to demonstrate that even low resolution macroscopic color measurements of a carefully designed test patch can yield misregistration estimates that are accurate up-to the sub-pixel level. The contributions of our work are as follows: 1.) a simple methodology to construct test patches that may be measured to obtain misregistration estimates, 2.) derivation of a reflectance printer model for the test patch so that color deviations in the spectral or reflectance space can be mapped to misregistration estimates, and 3.) a practical method to estimate misregistration via scanner RGB measurements. Experimental results show that our method achieves accuracy comparable to the state-of-the art but expensive geometric methods that are currently used by high-end color printing devices to estimate misregistration.

CMYK color separation is a technique commonly used in printing to reproduce mutli-color images. However, the color planes are generally not perfectly aligned with respect to each other when they are rendered by the imaging stations. This phenomenon, called color plane mis-registration, causes gap and halo artifacts. Trapping algorithms aim to reduce these artifacts by scanning through an image, determining the edges susceptible to mis-registration errors, and moving the edge boundaries of the lighter colorants underneath the edge boundaries of the darker colorants. In this paper, we propose a low-complexity approach to automatic color trapping which hides the effects of small color plane mis-registrations without negatively affecting the overall quality of the printed image.

The Yule-Nielsen modified spectral Neugebauer model enables predicting reflectance spectra from surface coverages. In order to provide high prediction accuracy, this model is enhanced with an ink spreading model accounting for physical dot gain. Traditionally, physical dot gain, also called mechanical dot gain, is modeled by one ink spreading curve per ink. An ink spreading curve represents the mapping between nominal to effective dot surface coverages when an ink halftone wedge is printed. In previous publications, we have shown that using one ink spreading curve per ink is not sufficient to accurately model physical dot gain, and that the physical dot gain of a specific ink is modified by the presence of other inks. We therefore proposed an ink spreading model taking all the ink superposition conditions into account. We now show that not all superposition conditions are useful and necessary when working with cyan, magenta, yellow, and black inks. We therefore study the influence of ink spreading in different superposition conditions on the accuracy of the spectral prediction model. Finally,

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 color halftone prints is introduced in this paper which considers these factors. The model is obtained by the extended Murray-Davies model and iterative algorithm. The model described in this paper contains two parameters, n and v . The n factor equals to the sum of w and v . The w factor relates to the optical spread function of paper relative to the spatial frequency of the halftone dots. The v factor relates to the distribution of colorant within the dots. The value of n and v are obtained by simulation according to the experimental data. For offset lithographic halftone data at 150lpi, the value of n and v are 1.578 and 0.02, thermal wax transfer halftone ( n =2.292, v =0.0209) and stochastic halftone ( n =1.1853, v =-0.006).

In this work, a novel approach for restoration of Color faded images is presented. A Uniform fading model is assumed. The algorithm comprises of matching the blocks in the image with some predefined reference blocks. These reference blocks are used to represent the true color of objects. The Correlation Coefficient is used as a measure for similarity matching. The threshold used for determining the matching is chosen adaptively from the image itself. A fade detection algorithm is proposed for distinguishing color faded images from the images with true cast. The algorithm has been tested and validated over a number of image sequences.