Peer Group Image Enhancement
 

C. Kenney, Y. Deng, B. S. Manjunath, and G. Hewer
 

Abstract

Peer group image processing identifies a "peer group" for
each pixel and then replaces the pixel intensity with the average over the
peer group. Two parameters provide directly control over which image fea-
tures are selectively enhanced: area (number of pixels in the feature) and
window diameter (window size needed to enclose the feature). A discussion
is given of how these parameters determine which features in the image are
smoothed or preserved. We show that the Fisher discriminant can be used
to automatically adjust the PGA parameters at each point in the image.
This local parameter selection allows smoothing over uniform regions while
preserving features like corners and edges. This adaptive procedure extends
to multilevel and color forms of PGA. Comparisons are made with
a variety of standard filtering techniques and an analysis is given of com-putational
complexity and convergence issues.