Nonlinear regression for image enhancement via generalized deterministic annealing

Scott Thomas Acton; Alan Conrad Bovik

doi:10.1117/12.157948

22 October 1993 Nonlinear regression for image enhancement via generalized deterministic annealing

Proceedings Volume 2094, Visual Communications and Image Processing '93; (1993) https://doi.org/10.1117/12.157948
Event: Visual Communications and Image Processing '93, 1993, Cambridge, MA, United States

Abstract

We introduce new classes of image enhancement techniques that are based on optimizing local characteristics of the image. Using a new optimization technique for nonconvex combinatorial optimization problems, generalized deterministic annealing (GDA), we compute fuzzy nonlinear regressions of noisy images with respect to characteristic image sets defined by certain local image models. The image enhancement results demonstrate the powerful approach of nonlinear regression and the low-cost, high-quality optimization of GDA.

Citation Download Citation

Scott Thomas Acton and Alan Conrad Bovik "Nonlinear regression for image enhancement via generalized deterministic annealing", Proc. SPIE 2094, Visual Communications and Image Processing '93, (22 October 1993); https://doi.org/10.1117/12.157948

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