In contrast to the Grand Alliance's HDTV Standard, which is incompatible with the existing TV standards, the author submits the digital stereo compatible TV standard (NTSC-DSC) which is completely compatible with the existing TV standards and advances a new image quality of TV -- its 3D stereo visualization making the stereo TV like real television when remote viewers can see from new stereo TV sets pictures in the same manner as they can see these pictures directly by their two eyes without TV. The main issues of the compatible stereo TV are multiplexing of the coupled stereo TV signals into one TV stereo signal compatible with the existing TV standard NTSC (PAL, SECAM), and digital video data compression as the tool to achieve such multiplexing. This paper is concentrated on the specific description of the method and technique of the digital video data compression of the one stereo ('left') TV signal and then time-division multiplexing of such highly compressed digital 'left' TV signal-file inside the other original analog NTSC 'right' TV signal. The essential stereo visual redundancy of the coupled TV signals reflects the fact that these stereo TV signals look like mainly the same, like 'twins.' If the stereo base of stereo binocular TV camera is along the TV line scanning, then there is a lot of identical, corresponding runs of pixels in both 'left' and 'right' TV signals for any TV scanning line. Such identical twins-runs are set apart by the shift along TV line depending on the distance to according image objects from the TV camera. The possibility of the time-division multiplexing based on the information emptiness for time intervals of the standard TV signal occupied by playbacks of TV scanning.

Automatic identification of textured surfaces is essential in many imaging applications such as image data compression and scene recognition. In these applications, a vision system is required to detect and identify irregular textures in the noisy color images. This work proposes a method for texture field characterization based on the local textural features. We first divide a given color image into n multiplied by n local windows and extract textural features in each window independently. In this step, the size of a window should be small enough so that each window can include only two texture fields. Separation of texture areas in a local window is first carried out by the Otsu or Kullback threshold selection technique on three color components separately. The 3-D class separation is then performed using the Fisher discriminant. The result of local texture classification is combined by the K-means clustering algorithm. The texture fields detected in a window are characterized by their mean vectors and an element-to-set membership relation. We have experimented with the local feature extraction part of the method using a color image of irregular textures. Results show that the method is effective for capturing the local textural features.

We present objective and subjective evaluations of five adaptive speckle reduction techniques: median filter, Lee multiplicative filter, geometrical filter, anisotropic diffusion and polynomial transform-based methods. For the objective evaluations we used several local and global measures of contrast and signal-to-noise ratio. For the subjective evaluation we used numerical scaling experiments assessing basic perceptual attributes. These are used to construct a multidimensional perceptual space subtended by perceptual attributes, namely noisiness, sharpness and contrast. These attributes, together with quality, are represented as vectors in the space. Results of the subjective evaluation show that quality of the processed images is mainly determined by the perception of noise, which in turn influences the perception of sharpness and contrast. The geometrical filter appears as the best filter in terms of objective measures, while the polynomial transform method is the best filter according to the subjective evaluation.

During the past decade, increasing use has been made of fractals to model natural phenomena and objects. The most widely used parameter is the fractal dimension; strictly speaking, a non-integer number between 1.0 and 2.0 for a linear object such as a coastline, and 2.0 and 3.0 for the surface of a solid object. A large number of algorithms have been developed for estimating fractal dimension, and it is not uncommon that these algorithms yield significantly different results when applied to the same data set. It is therefore of considerable importance to understand the true nature of the object being modeled, and to use the most appropriate algorithm for the particular application. A number of algorithms have been examined for use in various applications such as environmental sciences, planetary observations, geology, meteorology, and medical diagnosis and research. Specific problems with using fractal analysis in these applications are addressed.

This paper presents an investigation of area-based image correlation under full perspective geometric distortion. Image matching techniques in the presence of geometric distortion modeled by affine transformations have been examined thoroughly in earlier work while this research investigates the effects of full-perspective distortion on spatial domain area-based matching techniques. With area- based techniques, there are two factors that heavily affect correlation accuracy; first, the amount of signal variation within the target window must be sufficient to provide detectable similarity of imagery and second, the amount of geometric distortion within the window must be small enough not to inhibit matching. Signal variation is increased by increasing the target window size while the effects of perspective geometric distortion are minimized through smaller target windows. Window dimensionality is appropriately adapted to accommodate these two conflicting effects. Window adaptation based on precomputed metrics is applied to extend distortion toleration. The image sets are derived from a tactical scenario and are geometrically transformed through planar assumptions by a nonaffine spatial mapping. The two images are then registered through different correlation techniques, the defining functions analyzed and limitations on the amount of perspective viewpoint change of an imaging system in an aerial tactical arena are given while still allowing proper image correspondence.

Video signal system performance can be compromised in a military aircraft cockpit management system (CMS) with the tailoring of vintage Electronics Industries Association (EIA) RS170 and RS343A video interface standards. Video analog interfaces degrade when induced system noise is present. Further signal degradation has been traditionally associated with signal data conversions between avionics sensor outputs and the cockpit display system. If the CMS engineering process is not carefully applied during the avionics video and computing architecture development, extensive and costly redesign will occur when visual sensor technology upgrades are incorporated. Close monitoring and technical involvement in video standards groups provides the knowledge-base necessary for avionic systems engineering organizations to architect adaptable and extendible cockpit management systems. With the Federal Communications Commission (FCC) in the process of adopting the Digital HDTV Grand Alliance System standard proposed by the Advanced Television Systems Committee (ATSC), the entertainment and telecommunications industries are adopting and supporting the emergence of new serial/parallel digital video interfaces and data compression standards that will drastically alter present NTSC-M video processing architectures. The re-engineering of the U.S. Broadcasting system must initially preserve the electronic equipment wiring networks within broadcast facilities to make the transition to HDTV affordable. International committee activities in technical forums like ITU-R (former CCIR), ANSI/SMPTE, IEEE, and ISO/IEC are establishing global consensus on video signal parameterizations that support a smooth transition from existing analog based broadcasting facilities to fully digital computerized systems. An opportunity exists for implementing these new video interface standards over existing video coax/triax cabling in military aircraft cockpit management systems. Reductions in signal conversion processing steps, major improvement in video noise reduction, and an added capability to pass audio/embedded digital data within the digital video signal stream are the significant performance increases associated with the incorporation of digital video interface standards. By analyzing the historical progression of military CMS developments, establishing a systems engineering process for CMS design, tracing the commercial evolution of video signal standardization, adopting commercial video signal terminology/definitions, and comparing/contrasting CMS architecture modifications using digital video interfaces; this paper provides a technical explanation on how a systems engineering process approach to video interface standardization can result in extendible and affordable cockpit management systems.

In this paper, we propose a hybrid video coder using the wavelet packet transform and motion compensation. To reduce the computational complexity of the wavelet packet decomposition, a novel criterion based on the rate- distortion function is proposed. After the wavelet packet transform, the successive quantization scheme and the adaptive arithmetic coder are applied for lossy wavelet coefficient compression. Extensive experiments have been carried to compare the embedded wavelet packet coder with the MPEG standard and the embedded pyramid wavelet coder. The proposed wavelet packet transform method has the best performance in terms of both visual quality and PSNR measurement.

Central visual defect results in loss of vision in the region of retina with the highest resolution. Due to central visual field loss, these patients experience difficulty in visual tasks such as reading and recognizing faces. Age related macular degeneration (ARMD) and juvenile macular degeneration (JMD), destroy the function of the central retina. NASA Johnson Space Center has developed an electronic remapper that can warp from one coordinate system to another on a television screen. The remapper was used in this study to redistribute visual images projecting on the macular lesion to the still functioning peripheral retina. The purpose of this study was to investigate whether remapping of reading material around the central scotomas of patients with ARMD and JMD improved reading rates. Reading rates of nonremapped words and remapped words were compared under three viewing conditions: (1) Reading without stabilization under free viewing condition, (2) Reading with image stabilization through the eye tracker, (3) Reading without image stabilization through the eye tracker.

Statistically based automatic design of nonlinear image processing algorithms has been used successfully for binary image enhancement, specifically in restoration and resolution conversion of documents. The present paper introduces an extension of the methodology in two directions. First, it proposes to use the representation- optimization paradigm for general algorithm development in the context of system transformations. Second, it employs a statistical loss function to generalize the mean-absolute- error approach taken in previous work.

For a staring-array imaging system the location of a scene edge can be reconstructed by digital techniques to a sub- pixel scale even if the image data is blurred, undersampled and noisy. In this paper three algorithms are presented for solving this sub-pixel edge reconstruction problem. The performance of these algorithms is analyzed by extensive model-based simulations using a comprehensive image formation system model that accounts for blurring, noise and sampling.

This article deals with the method analogous to photographic ones for determination of ultimate-resolved spatial frequency over a sine wave object. In these methods a resolution is searched graphically on a crossing of MTF curve with that of threshold contrast of a photographic material. A method of phase modulation of computer synthesized harmonic signal is offered. Digital image obtained with the help of the analyzed optical-electronic system is used. The digital image is previously differentiated and rationed. The modulated signal may be visualized, it will be seen on a monitor in a form of modulation bands. With increasing of frequency of a sine wave signal the visual perception of modulation bands will be worsened due to random character of modulation signal. This property is used to evaluate the ultimate-resolved spatial frequency. Methods of correlation analysis and methods of analysis in frequency area for automation of estimation process of ultimate-resolved frequency are discussed. Results of quality and quantity analysis for real images are presented.

Infrared images have low resolution and obscure details. Many 3D reconstruction methods from visual images are unsuitable for infrared images. In this paper, a method of 3D reconstruction from infrared images is presented. This method is based on volume intersection technique and 3D object representation is octree structure. Octree representation is compact, informative and especially useful for graphic displays and object recognition tasks.

This paper concerns the determination of structure and pose of 3-D bilateral symmetric objects from a single perspective view. A novel algebraic algorithm is described. The unknown structure and pose parameters are determined in three steps. The algorithm first recovers the three rotation angles, then the three translation parameters, and finally the object shape. Computation at all steps is linear and in closed- form. The determination of the rotation angles requires no knowledge about the size of the object, whereas the translation and shape can only be recovered up to a global scale without a priori knowledge of the object dimension.

The texture discrimination properties of a directional operator, using a window based histogram correlation technique, are described for test images and natural scene imagery. The natural image examples are drawn from digitized monochrome aerial photographs of volcanic terrain, and of coastal dune fields in the region of West Lancashire, England. The operator masks use directionally encoded local difference parameters and are of two sizes, 3 by 3 and 2 by 2 pixels, scanning over a window size of 25 by 25 pixels to create an autocorrelation map, normalized to the output gray-scale range. Comparisons of the outputs are discussed in terms of ability to detect specific types of texture feature associated with known lava flow regimes demonstrate the viability of the technique down to single pixel resolution, particularly for folded or striated topography. The vegetation cover of the volcanic terrain is also characterized in terms of its response to these texture operators. The output from the dune field images, which contain a wider variety of vegetation cover, also demonstrates the discrimination capability of the technique and its potential usefulness in environmental and conservation management.

Objectivity, measurement accuracy and repeatability are compromised whenever the human vision system is involved in assessing the performance of optical and electro-optical components. One example of this is found in the inspection of image intensifier tubes (IITs). This paper discusses the use of an automated intensifier measurement system (AIMS), that was developed to overcome the drawbacks of the subjective evaluation methods currently in use. The AIMS offers significant improvement over visual inspection techniques typically performed by a human operator. The AIMS quantifies an IIT's performance in a number of categories including: resolution, geometric image distortion, output brightness uniformity (opaque and bright spots), and image format; measurement accuracy is traceable to NIST. Innovative image-processing techniques allow precise characterization of the entire IIT using an off-the-shelf CCD that can capture the complete intensified image without employing scanning or magnifying techniques. The system also performs a self test to ensure correct setup. Now for the first time, because all the necessary setup adjustments and measurements are performed under software control, all subjectivity is eliminated, allowing totally objective measurements to be made. System performance results are discussed.