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Proceedings Paper

Visual-system-based polar quantization of local amplitude and local phase of orientation filter outputs
Author(s): Bernhard Wegmann; Christoph Zetzsche
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Paper Abstract

Image decomposition via even- and odd-symmetric, size and orientation selective band-pass filters, as suggested by the receptive field properties of visual cortical neurons, is well suited to image coding purposes. Interpretation of the even/odd filter outputs as a complex ("analytic") signal offers the alternative of a polar signal representation by a local amplitude and a local phase component. This is also indicated by our measurement of a rotation symmetric shape of the two-dimensional probability density function (pdf) of the even/odd filter outputs. Our investigations into the properties of such a representation show that it provides an interesting separation of the "amount of signal variation" (local amplitude) vs. the "type of signal variation" (local phase) . Furthermore an efficient vector quantization procedure can be applied to the two-dimensional amplitude/phase vector. This procedure divides the 2D signal space of the analytic signal into polar separable patches. Since phase quantization errors are more tolerable at small amplitude levels local phase is quantized dependent on the amplitude level. While typical pdf-optimized quantizers produce an increasingly higher amplitude resolution towards very small amplitudes, human vision allows the application of an appropriate threshold which leads to an "irrelevance zone" wherein obviously no phase information has to be coded. Using this coding scheme good image quality can be obtained with about 0.8 bit/pixel.

Paper Details

Date Published: 1 October 1990
PDF: 12 pages
Proc. SPIE 1249, Human Vision and Electronic Imaging: Models, Methods, and Applications, (1 October 1990); doi: 10.1117/12.19680
Show Author Affiliations
Bernhard Wegmann, Technische Univ. Muenchen (Germany)
Christoph Zetzsche, Technische Univ. Muenchen (Germany)

Published in SPIE Proceedings Vol. 1249:
Human Vision and Electronic Imaging: Models, Methods, and Applications
Bernice E. Rogowitz; Jan P. Allebach, Editor(s)

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