Adaptive estimators for filtering noisy images

Balakrishnan Mahesh; Woo-Jin Song; William A. Pearlman

doi:10.1117/12.55617

1 May 1990 Adaptive estimators for filtering noisy images

Balakrishnan Mahesh, Woo-Jin Song, William A. Pearlman

Author Affiliations +

Optical Engineering, Vol. 29, Issue 5, (May 1990). https://doi.org/10.1117/12.55617

Abstract

A new estimation criterion called the minimum-error minimum correlation (MEMC) criterion is implemented in conjunction with an adaptive windowing technique. The image statistics are calculated within the window, the dimensions of which vary depending on the local statistics. The MEMC estimator produces sharper and hence visually more pleasing restorations, while the adaptive windows tend to isolate regions of the image that are locally stationary. Since most of the error after restoration is in the vicinity of edges, a postprocessing step of filtering along the edges is applied. These image restorations are compared to both fixed and adaptive minimum mean squared error estimators.

Citation Download Citation

Balakrishnan Mahesh, Woo-Jin Song, and William A. Pearlman "Adaptive estimators for filtering noisy images," Optical Engineering 29(5), (1 May 1990). https://doi.org/10.1117/12.55617

Published: 1 May 1990

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