Multiple Regression Analysis Approach To The Automatic Design Of Adaptive Image Processing Systems

N. Otsu

doi:10.1117/12.936972

9 January 1984 Multiple Regression Analysis Approach To The Automatic Design Of Adaptive Image Processing Systems

N. Otsu

Proceedings Volume 0435, Architectures and Algorithms for Digital Image Processing; (1984) https://doi.org/10.1117/12.936972
Event: 27th Annual Technical Symposium, 1983, San Diego, United States

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.

Citation Download Citation

N. Otsu "Multiple Regression Analysis Approach To The Automatic Design Of Adaptive Image Processing Systems", Proc. SPIE 0435, Architectures and Algorithms for Digital Image Processing, (9 January 1984); https://doi.org/10.1117/12.936972

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