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Proceedings Paper

Numerical Analysis of Image Patterns
Author(s): Alan C. Bovik; Nanda Gopal; Tomas Emmoth
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Paper Abstract

We find similarities between spatial pattern analysis and other low-level cooperative visual processes. Numerical algorithms for computing intrinsic scene attributes, e.g. shape-from-X (shading, texture, etc.) and optical flow typically involve estimating generalized orientation components via iterative constraint propagation. Smoothing or regularizing terms imposed on the constraint equations often enhance the uniqueness / stability (well-posedness) of the solutions. The numerical approach to visual pattern analysis developed here proceeds analogously via estimation of emergent 2-D image frequencies. Unlike shape-from-X or optical flow paradigms, constraints are derived from the responses of multiple oriented spatial frequency channels rather than directly from the image irradiance measurements. By using channel filters that are sufficiently concentrated in both space and frequency, highly accurate spatial frequency estimates are computed on a local basis. Two methods are proposed. In the first, constrained estimates of the emergent image frequencies are obtained by resolving the responses of multiple channel filters in a process similar to photometric stereo. The second approach formulates the estimation of frequencies as an extremum problem regularized by a smoothing term. An iterative constraint propagation algorithm is developed analogous to those used in variational / relaxational approaches to shape-from-X (shading, texture) and optical flow. Examples illustrate each approach using synthetic and natural images.

Paper Details

Date Published: 1 November 1989
PDF: 14 pages
Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); doi: 10.1117/12.970131
Show Author Affiliations
Alan C. Bovik, The University of Texas at Austin (United States)
Nanda Gopal, The University of Texas at Austin (United States)
Tomas Emmoth, The University of Texas at Austin (United States)

Published in SPIE Proceedings Vol. 1199:
Visual Communications and Image Processing IV
William A. Pearlman, Editor(s)

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