On Fuzzy Nonlinear Regression for Image Enhancement
Scott, T. Acton
Journal of Mathematical Imaging and Vision 8(3): 239-253
ISSN/ISBN: 0924-9907 DOI: 10.1023/a:1008222617999
Nonlinear regression analysis with respect to fuzzy characteristic sets, or fuzzy nonlinear regression, is a potentially useful and previously unexplored digital signal processing tool. Here, the fuzzy regression model is used in the image enhancement problem. Given a noisy image, the noise is eliminated by computing a regression- the "closest" image to the input image that has membership in the characteristic set. The known properties of the original, uncorrupted imagery (e. g., smoothness) are used to define membership in the characteristic set. With conventional crisp characteristic sets that enforce the characteristic property in a global sense, the local image structure may be sacrificed.