Computer-generated noise images for the evaluation of image processing algorithms

Details Computer-generated noise images for the evaluation of image processing algorithms Computer-generated noise images for the evaluation of image processing algorithms

May 1993

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1993opten..32..982w&link_type=abstract

Optical Engineering 32(05), 982-992, Brian J. Thompson; Ed.

Statistics

Applications

5

Scientific paper

Effective implementation of image processing algorithms for enhancement and restoration often assumes that the images are degraded by known statistical noise. Depending on the application, the type of noise present may vary. The noise distributions that are commonly encountered in image processing are the Gaussian, Rayleigh, negative exponential, and gamma. Typically, when computer-generated noise images are used for algorithm development they are spatially uncorrelated. It is the purpose of this paper to present various types of computer-generated two-dimensional correlated and uncorrelated noise images along with suggestions of several applications.

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