Optimum intensity-dependent spread filters in image processing

Matt Mehrzad Vaezi; Behnam Bavarian; Glenn Healey

doi:10.1117/12.45371

1 June 1991 Optimum intensity-dependent spread filters in image processing

Matt Mehrzad Vaezi, Behnam Bavarian, Glenn Healey

Proceedings Volume 1452, Image Processing Algorithms and Techniques II; (1991) https://doi.org/10.1117/12.45371
Event: Electronic Imaging '91, 1991, San Jose, CA, United States

Abstract

The class of Intensity-Dependent Spread (IDS) filters proposed by Cornsweet and Yellott produces the reflectance ratio map at the output of the filter independent of illumination. We propose a new method to optimize the spread function in the context of the IDS filters. The optimum spread is the solution to a variational formulation where the image noise is minimized subject to a smoothness constraint. In our solution, the Lagrangian parameter is space-dependent and also is inversely proportional to the spread function. This solution is a function of the input image and its first and second derivatives. The optimized scale-function is then applied to the IDS filter structure to produce sharp edge localization as well as reflectance ratio estimates independent of illumination. The simulation results illustrate the fact that the Optimum Intensity-Dependent Spread filter improves the performance of the IDS filter and also is two orders of magnitude faster for 512 X 512 images. Examples comparing the results of the two filter structures are illustrated.

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Matt Mehrzad Vaezi, Behnam Bavarian, and Glenn Healey "Optimum intensity-dependent spread filters in image processing", Proc. SPIE 1452, Image Processing Algorithms and Techniques II, (1 June 1991); https://doi.org/10.1117/12.45371

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KEYWORDS

Optical filters

Image filtering

Image processing

Retina

Gaussian filters

Reflectivity

Computer engineering

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