Showing papers by "Alan C. Bovik published in 1991"

Method and apparatus for processing both still and moving visual pattern images

Abstract: An improved method for coding and decoding still or moving visual pattern images by partitioning images into blocks or cubes, respectively, and coding each image separately according to visually significant responses of the human eye Coding is achieved by calculating and subtracting a mean intensity value from digital numbers within each block or cube and detecting visually perceivable edge locations within the resultant residual sub-image If a visually perceivable edge is contained within the block or cube, gradient magnitude and orientation at opposing sides of the edge within each edge block or cube are calculated and appropriately coded If no perceivable edge is contained within the block or cube, the sub-image is coded as a uniform intensity block Decoding requires receiving coded mean intensity value, gradient magnitude and pattern code, and then decoding a combination of these three indicia to be arranged in an orientation substantially similar to the original digital image or original sequence of digital images Coding and decoding can be accomplished in a hierarchical pattern Further, hierarchical processing can be programmably manipulated according to user-defined criteria

Using chromatic information in edge-based stereo correspondence

Abstract: One approach to developing a faster, more robust solution to the stereo correspondence problem is to seek a more complete and efficient use of available image information. Motivated by the observation that chromatic (color) information is a salient, regional property of surfaces in many natural scenes, the goal of this research has been to gain a fundamental understanding of the use of chromatic information in edge-based stereo correspondence. In particular, the use of chromatic information to characterize intensity edges is analyzed, and the chromatic gradient matching constraint, which specifies disambiguation criteria for edge-based stereo correspondence, is developed. The result is a theoretical construction for developing edge-based stereo correspondence algorithms which use chromatic information. The efficacy of using chromatic information via this construction is demonstrated by implementing a disparity-gradient-based algorithm and comparing algorithm performance with and without the chromatic gradient matching constraint. The results demonstrate that the use of chromatic information can significantly reduce the ambiguity between potential matches, resulting in increased algorithm accuracy as well as increased algorithm speed.

Scanning electrochemical microscopy. 11. Improvement of image resolution by digital processing techniques

Abstract: Images obtained by scanning electrochemical microscopy (SECM) were improved (deblurred) by use of digital image processing techniques, i.e., a linear combination of Laplacian and Gaussian filtering. Image improvement of repetitive structure (minigrid; interdigitated arrays) and an irregular structure (the bottom surface of a Ligustrum sinense leaf) is described.

Three-dimensional orientation from texture using Gabor wavelets

Abstract: We present a method for measuring the three-dimensional orientation of planar surfaces. We derive a model relating the spatially varying instantaneous frequency of the image texture to the instantaneous frequency of the surface texture, to the orientation of the surface, and to the parameters of the imaging system. We measure the localized frequency at each image point with Gabor wavelets and use it to solve for the surface orientation according to the model. The method does not require the extraction of discrete texture elements. The algorithm has a mean error of about 5 degrees in the measured slant and tilt on a test set of 12 real-world surfaces.© (1991) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Neural Networks for Textured Image Processing

Abstract: We review key conventional and neural network techniques for processing of textured images, and highlight the relationships among different methodologies and schemes. Texture, which provides useful information for segmentation of scenes, classification of surface materials and computation of shape, is exploited by sophisticated biological vision systems for image analysis. A brief overview of biological visual processing provides the setting for this study of textured image processing. We explain the use of multiple Gabor filters for segmentation of textured images based on a locally quasimonochromatic image texture model. This approach is compared to the functioning of localized neuronal receptive fields. Cooperative neural processes for perceptual grouping and emergent segmentation are reviewed next, and related to relaxation labelling. The recently developed SAWTA neural network for texture-based segmentation is then presented. Finally, techniques for describing and processing texture as a constrained optimization problem are outlined.

Windowed locally monotonic regression

Abstract: Lomotonicity, the largest degree of local monotonicity that a signal has, is proposed as an appropriate measure of smoothness when studying smoothers such as the median filter. Locally monotonic regression (LMR) optimally solves the problem of smoothing a signal to a specified minimal degree of lomotonicity, but it often requires an excess of computational resources. Windowed locally monotonic regression (WLMR) presents an attractive alternative to the problem of smoothing signals under the smoothness criterion of lomotonicity. This criterion is meaningful, for example, when processing images and speech signals. Unlike LMR, WLMR is defined also for infinite-length signals; this may be useful in more theoretical studies of this tool. >

Digital restoration of scanning electrochemical microscope images

Abstract: Images obtained from the scanning electrochemical microscope (SECM) have been restored by digital computer techniques. SECM images are inherently blurred by the diffusion process that occurs in the oxidation-reduction reaction at the probe tip. Restoration of an image of the bottom surface of a Ligustrum sinensis leaf as well as the image of a conductive inverse indium tin oxide grid structure is described here. The authors present two techniques for restoring SECM images. The first is an inverse filtering technique and the second is a smoothed Taylor series approximation of the unblurred image via a modification of a procedure given in Rosenfeld and Kak.

Nonuniform visual pattern image sequence coding

Abstract: Visual Pattern Image Sequence Coding (VPISC) is a pyramidal image coding scheme which utilizes human visual system (HVS) properties to achieve low bit rates while maintaining a good perceived image quality, all with extremely low computational cost. This paper describes extensions of VPISC, termed Foveal VPISC (FVPISC) and Adaptive VPISC (AVPISC). Both algorithms produce decreased bit rates by selectively allowing some image regions to be coded at low resolution. In FVPISC, a foveation criterion is used to select a region of interest. In AVPISC, the algorithm adaptively determines which regions require high-resolution coding in order to maintain uniform image quality over the entire image.

Dense stereo correspondence using color

Abstract: We investigate the use of chromatic information in dense stereo correspondence. Specifically the chromatic photometric constraint which is used to specify a mathematical optimality criterion for solving the dense stereo correspondence problem is developed. The result is a theoretical construction for developing dense stereo correspondence algorithms which use chromatic information. The efficacy of using chromatic information via this construction is tested by implementing singleand multi-resolution versions of a stereo correspondence algorithm which uses simulated annealing as a means of solving the optimization problem. Results demonstrate that the use of chromatic information can significantly improve the performance of dense stereo correspondence. 1.© (1991) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A bound involving n-dimensional instantaneous frequency

Abstract: The author states and proves an integral inequality that bounds the absolute difference epsilon (x)= mod m(x) -m(x) mod where m(x) is the response of a modulated n-dimensional real linear filter w to a complex exponential signal with n-dimensional instantaneous frequency Delta u(x) and m(x)= mod W( Delta u(x)-u/sub 0/) mod where W is the Fourier transform of w. The quantity of epsilon (x) provides an estimate of the error incurred by using m(x) as an estimate of m(x), e.g., if Delta u(x) is unknown. Such estimates may be applied to the problem of measuring the n-dimensional instantaneous frequency of certain nonstationary phase-modulated signals. >

Dense stereo correspondence using color

Abstract: We investigate the use of chromatic information in dense stereo correspondence. Specifically, the chromatic photometric constraint, which is used to specify a mathematical optimality criterion for solving the dense stereo correspondence problem, is developed. The result is a theoretical construction for developing dense stereo correspondence algorithms which use chromatic information. The efficacy of using chromatic information via this construction is tested by implementing singleand multi-resolution versions of a stereo correspondence algorithm which uses simulated annealing as a means of solving the optimization problem. Results demonstrate that the use of chromatic information can significantly improve the performance of dense stereo correspondence.