The major limitations of precise evaluation of retinal structures in present clinical situations are the lack of standardization, the inherent subjectivity involved in the interpretation of retinal images, and intra- as well as interobserver variability. While evaluating optic disc deformation in glaucoma, these limitations could be overcome by using advanced digital image analysis techniques to generate precise metrics from stereo optic disc image pairs. A digital stereovision system for visualizing the topography of the optic nerve head from stereo optic disc images is presented. We have developed an algorithm, combining power cepstrum and zero-mean-normalized cross correlation techniques, which extracts depth information using coarse-to-fine disparity between corresponding windows in a stereo pair. The gray level encoded sparse disparity matrix is subjected to a cubic B-spline operation to generate smooth representations of the optic cup/disc surfaces and new three-dimensional (3-D) metrics from isodisparity contours. Despite the challenges involved in 3-D surface recovery, the robustness of our algorithm in finding disparities within the constraints used has been validated using stereo pairs with known disparities. In a preliminary longitudinal study of glaucoma patients, a strong correlation is found between the computer-generated quantitative cup/disc volume metrics and manual metrics commonly used in a clinic. The computer generated new metrics, however, eliminate the subjective variability and greatly reduce the time and cost involved in manual metric generation in follow-up studies of glaucoma.

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A new holographic implementation of a sampling technique permits, in principle, a straightforward representation of 2-D space-variant optical systems. The set of sample transfer functions required for the representation is recorded on a single holographic plate by utilizing phase coded reference beams. Because this approach does not depend on volume effects in the recording medium in an essential way, the holograms can be produced digitally, as well as optically. Basic concepts and preliminary experimental investigations related to this approach are presented and discussed.

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The performance of an image compression scheme is affected by the presence of noise, and the achievable compression may be reduced significantly. We investigated the effects of specific signal-dependent-noise (SDN) sources, such as film-grain and speckle noise, on image compression, using JPEG (Joint Photographic Experts Group) standard image compression. For the improvement of compression ratios noisy images are preprocessed for noise suppression before compression is applied. Two approaches are employed for noise suppression. In one approach an estimator designed specifically for the SDN model is used. In an alternate approach, the noise is first transformed into signal-independent noise (SIN) and then an estimator designed for SIN is employed. The performances of these two schemes are compared. The compression results achieved for noiseless, noisy, and restored images are also presented.