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Proceedings Paper

Multiple Regression Analysis Approach To The Automatic Design Of Adaptive Image Processing Systems
Author(s): N. Otsu
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Paper Abstract

Multiple regression analysis for modeling the correspondence between a set of input variates and an output variate or a set of variates seems to be one of the most promising and direct approaches to automatically designing adaptive (or learning) systems for image pro-cessing and computer vision. Some approaches are shown with experimental results, such as automatic design of adaptive filters for image enhancement and restoration by giving the input image and the desired out-put image as a pair. The advantage of such an approach is the capability to simulate in an automatic and gen-eral way the functional "black boxes" (solutions) which are imposed by real problems regard-less of their inner detail, while the usual approaches are based on the so-called trial and error methods where any method proposed is repeatedly tried and checked for its results.

Paper Details

Date Published: 9 January 1984
PDF: 6 pages
Proc. SPIE 0435, Architectures and Algorithms for Digital Image Processing, (9 January 1984); doi: 10.1117/12.936972
Show Author Affiliations
N. Otsu, Electrotechnical Laboratory (Japan)

Published in SPIE Proceedings Vol. 0435:
Architectures and Algorithms for Digital Image Processing
Per-Erik Danielsson; Andre J. Oosterlinck, Editor(s)

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