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Griswold, N. C.

Publications and source records attributed to Griswold, N. C..

A modification of the fusion model for log polar coordinates

The fusion mechanism for application in stereo analysis of range restricted the depth of field and therefore required a shift variant mechanism in the peripheral area to find disparity. Misregistration was prevented by restricting the disparity detection range to a neighborhood spanned by the directional edge detection filters. This transformation was essentially accomplished by a nonuniform resampling of the original image in a horizontal direction. While this is easily implemented for digital processing, the approach does not (in the peripheral vision area) model the log-conformal mapping which is known to occur in the human mechanism. This paper therefore modifies the original fusion concept in the peripheral area to include the polar exponential grid-to-log conformal tesselation. Examples of the fusion process resulting in accurate disparity values are given.

Griswold, N. C.↗

Disparity coding - An approach for stereo reconstruction

As the possibility of stereo-controlled robots becomes a reality, the need to transmit the stereo pair of images to a ground station or space station for man-in-the-loop supervision will be a necessity. The complexity of transmitting stereo images by coding the preprocessed disparity is presently discussed. The approach demonstrates the quantization, modulation, and reconstruction of the stereo images. Results indicate the accuracy of reconstruction in terms of mean-square-error criterion as a function of the signal-to-noise ratio. Key research issues of interpolation from sparse disparity maps and reconstruction of the stereo pairs in the presence of spatial noise are presented. It is concluded that stereo reconstruction is possible, and the noise constraints are given.

Griswold, N. C.↗

A stereo model based upon mechanisms of human binocular vision

A model for stereo vision, which is based on the human-binocular vision system, is proposed. Data collected from studies of neurophysiology of the human binocular system are discussed. An algorithm for the implementation of this stereo vision model is derived. The algorithm is tested on computer-generated and real scene images. Examples of a computer-generated image and a grey-level image are presented. It is noted that the proposed method is computationally efficient for depth perception, and the results indicate accuracies that are noise tolerant.

Griswold, N. C.↗