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The problem of identifying three dimensional objects from their two dimensional perspective projections is an important one in computer vision. A segmentation procedure is described here to extract features from a simulated image, then a matching procedure which finds the three dimensional objects in the picture is discussed. An image: a photograph taken by a camera with fixed focal length, is given, and a three dimensional wire frame object model is also given. Each object in the model is composed of planar arcs. The arc is bounded by connected line segments or conics. The input image is a simulated photographs of some objects of our model, the problem is to identify what these objects are. The two dimensional data structure we derived from image are equations of each planar arc. The data stored in the database are equations of the boundary pieces of the three dimensional object. Our aim is to find the match between the given three dimensional data structure and the two dimensional data structure. The method used here is a numerical analysis nonlinear optimization. / Ph. D.

Image data compression is an active topic of research in image processing. Traditionally, most image data compression schemes have been dominated by digital processing due to the fact that digital systems are inherently flexible and reliable. However, it has been demonstrated that optical processing can be used for spatial image data compression, using a method called interpolated differential pulse code modulation (IDPCM). This is a compression scheme which functions analogously with conventional digital DPCH compression, except that the specific compression steps are implemented by incoherent optical processing. The main objective of this research is to extend IDPCM to interframe compression, design such systems, and evaluate the compression performance limitation under no channel errors, given the subjectively acceptable image quality by means of digital simulation. We start with a review of digital spatial and interframe compression techniques and their implications for optical implementation. Then, the technological background of electro-optical devices which has made possible hybrid optical/digital processing for image data compression will be briefly discussed. Also, a detailed description of IDPCM coding is given, along with the ways that IDPCM can be extended to interframe compression. Finally, two architectures of hybrid and optical/digital interframe compression are proposed, simulated, and evaluated in order to discover potential performances of optically implemented interframe compression systems. Excellent reconstructed image quality is obtained by the proposed adaptive hybrid (O/D) IDPCM/frame replenishment technique at an overall transmission rate of 3 Mbits/sec, average bit rate of 1.5 bits/pixel, and the average compression ratio of 5.2:1.

The main thrust of this dissertation is the application of statistics and information theory to design, analysis and estimation pertaining to image-forming systems. This study explores the application of Shannon's information in pupil design, the characterization of noise, and study of its behavior in a specific electro-optical system, and estimation of the degraded spread function in atmospherical imagery using the maximum entropy method. Our study shows that a pupil designed to maximize Shannon's information throughput is an apodizer, resulting in resolution and contrast enhancement when compared to the diffraction-limited case. The Strehl ratio is about 0.55. Investigation of statistical and spectral properties as a function of gray level in an electro-optical tracking system indicates that the noise is "white," having a wide band and a close-to-Gaussian distribution. Estimating the spread function via maximum entropy technique has revealed some remarkable results. Using an edge as the object, simulation studies predict a superior estimate in the mean squared error sense to those of the least squares in the presence of three types of noise (signal-dependent Gaussian and Poisson, and signal-independent Gaussian noise). Information theory, linear systems theory, sampling theory and more particularly, statistics and the Fast Fourier Transform are used to derive our results.

The fundamental components for processing all-optically represented data, namely optical switches and logic gates are investigated. Improved techniques for fabricating nonlinear Fabry-Perot etalons containing GaAs have brought a proliferation of GaAs optical bistable devices. These devices show significant improvements in speed, power requirements, operating temperature and thermal stability. Experiments verify predictions that one can operate a single nonlinear etalon as optical logic gates or two such etalons as a flip-flop. Optimization of the logic gates is then discussed from a systems approach.

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