Peer group image enhancement

Author

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

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA

Volume

10

Issue

2

fYear

2001

fDate

2/1/2001 12:00:00 AM

Firstpage

326

Lastpage

334

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 direct control over which image features 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 peer group averaging (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 computational complexity and convergence issues

Keywords

computational complexity; convergence of numerical methods; image enhancement; nonlinear filters; smoothing methods; Fisher discriminant; PGA parameters; adaptive procedure; area parameter; computational complexity; convergence; corners preservation; edges preservation; filtering techniques; image enhancement; image smoothing; local parameter selection; peer group averaging; peer group image processing; uniform regions; window diameter; Additive noise; Electronics packaging; Entropy; Filtering; Image coding; Image enhancement; Image processing; Pixel; Predictive models; Smoothing methods;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.902298

Filename

902298