Harley R. Myler

Practical considerations on color image enhancement using homomorphic filtering

We present a study concerning the practical possibilities of using the homomorphic filtering for color image enhancement. Two of the most popular color models, RGB and C-Y (color difference), are employed and the results are comparatively discussed. The homomorphic filtering has proven to be a viable tool for both color models considered.

Multicriterion vehicle pose estimation for SAR ATR

Many approaches to target recognition on SAR images employ model-based techniques. These systems incorporate computationally intensive operations such as large database probing or complex 3D renderings that are used to produce simulations that are compared against unknown targets. These operations would achieve a significant improvement in speed performance if the target poses were known in advance. A study that addresses the problem of estimating the poses of vehicles in SAR images is reported in this paper. A pose estimation algorithm suite is proposed that is based on a set of partially independent criteria. A statistical analysis of the performance obtained by employing the established criteria, both individually and in combination, is also conducted and the results are comparatively discussed.

Gabor difference analysis of digital video quality

The rapid increase in the development of digital video systems has generated a strong need for objective video quality metrics. Two methods are presented in this work. One is the Gabor difference analysis (GDA) full reference method, and the other is the reverse frame prediction (RFP) no reference video quality method. Both methods are based on the multi-channel properties of the human visual system (HVS). Gabor filtering is used in both methods. In the GDA method, a reference and a degraded digital video sequence are compared by taking into account various psycho-perceptual properties of the HVS. The RFP method does not require a reference video stream and is intended for in-service testing and on-line monitoring. The performances of the proposed methods are evaluated. The methods in this work are shown to be consistent with the data from subjective testing over a wide range of scenes. This work is critical to the evaluation of the effectiveness of compression schemes on HDTV imagery.

Computer-generated noise images for the evaluation of image processing algorithms

Effective implementation of image processing algorithms for enhancement and restoration often assumes that the images are degraded by known statistical noise. Depending on the application, the type of noise present may vary. The noise distributions that are commonly encountered in image processing are the Gaussian, Rayleigh, negative exponential, and gamma. Typically, when computer-generated noise images are used for algorithm development they are spatially uncorrelated. It is the purpose of this paper to present various types of computer-generated two-dimensional correlated and uncorrelated noise images along with suggestions of several applications.

Edge detection of color images using the HSL color space

Various edge detectors have been proposed as well as several different types of adaptive edge detectors, but the performance of many of these edge detectors depends on the features and the noise present in the grayscale image. Attempts have been made to extend edge detection to color images by applying grayscale edge detection methods to each of the individual red, blue, and green color components as well as to the hue, saturation, and intensity color components of the color image. The modulus 2(pi) nature of the hue color component makes its detection difficult. For example, a hue of 0 and 2(pi) yields the same color tint. Normal edge detection of a color image containing adjacent pixels with hue of 0 and 2(pi) could yield the presence of an edge when an edge is really not present. This paper presents a method of mapping the 2(pi) modulus hue space to a linear space enabling the edge detection of the hue color component using the Sobel edge detector. The results of this algorithm are compared against the edge detection methods using the red, blue, and green color components. By combining the hue edge image with the intensity and saturation edge images, more edge information is observed.

Histogram specification of 24-bit color images in the color difference (C-Y) color space

Histogram equalization and specification have been widely used to enhance the content of grayscale images, with histogram specification having the advantage of allowing the output histogram to be specified as compared to histogram equalization which attempts to produce and output histogram which is uniform. Unfortunately, extending histogram techniques to color images is not very straightforward. Performing histogram specification on color images in the RGB color space results in specified histograms that are hard to interpret for a particular enhancement that is desired. Human perception of color interprets a color in terms of its hue, saturation, and intensity components. In this paper, we describe a method of extending graylevel histogram specification to color images by performing histogram specification on the luminance (or intensity), saturation, and hue components in the color difference (C-Y) color space. This method takes into account the correlation between the hue, saturation, and intensity components while yielding specified histograms which have physical meaning. Histogram specification was performed on an example color image and was shown to enhance the color content and details within this image without introducing unwanted artifacts.

The architecture of an inexpensive and portable talking-tactile terminal to aid the visually handicapped

Abstract The visually handicapped computer user of programmer is faced with a very difficult task in interfacing with computing hardware. The types of equipment currently available for this purpose fall into one of several general categories: expensive, nonportable and domain-specific. In the current research proposal, we describe a new terminal device designed specifically for the visually handicapped that answers all of the problems mentioned above. The work is already under way, with a prototype model currently in use by a visually handicapped programmer on the development team. In the remainder of this paper, we will present a report on the current status of our project as well as plans and milestones for future work.

Iterative multiresolution algorithm for image reconstruction from the magnitude of its Fourier transform

Iterative algorithms are currently the most effective approaches to solving a number of difficult signal reconstruction and recovery problems, and all of these algorithms suffer from stagnation and computational complexity. We propose a new multiresolution iterative approach that employs the concept of a multiresolution pyramid. This method attempts to solve the problem of image reconstruction from the measurement of the image’s Fourier modulus by decomposing the problem onto different resolution grids, which enables the iterative algorithm to avoid stagnation by providing a better initial guess and enabling a higher likelihood of arriving at a global minimum while dramatically reducing the computational cost. Results on both synthetic and real-world images are shown; a performance comparison with the direct iterative algorithm demonstrates the effectiveness of our approach in terms of convergence, robustness and computational efficiency.

Nonlinear image transformations implemented with spatial light modulators

A technique for optically implementing nonlinear gray-level transformations on images via a spatial light modulator (SLM) coupled to a computer image-processing system is presented. Both the exponential and the logarithmic functions are implemented. The only restriction in the choice of nonlinear transformations is that they must lie below the SLMs linear intensity output versus intensity input curve obtained with the SLM set to a full transmittance.

Characterization of disagreement in multiplatform and multisensor fusion analysis

An interesting problem arises in multi platform-multisensor information fusion system when sources disagree on the classification or identity of an unknown entity. If there is disagreement, the ideal situation ins a high level of confidence form a single source with complete disagreement in the remaining sources. This is not always the case and situations may arise where the winner is only successful by a small margin and there is collective disagreement amongst the losing sources. This paper describes a new terminology, disfusion, which is used for the characterization of disagreement between information sources and can enhance the final conclusion of a fusion system.