Fuzzy transformation and its applications

Author

Nie, Yuo ; Barner, K.E.

Author_Institution

Dept. of Electr. & Comput. Eng., Delaware Univ., Newark, DE, USA

Volume

1

fYear

2003

fDate

14-17 Sept. 2003

Abstract

In this paper, we introduce the basic concepts of the fuzzy transformation (FZT) theory and their applications in image denoising. FZT is a data-adaptive nonlinear transformation, where the transformation matrix is a dynamic real-valued spatial-rank (SR) matrix (i.e., fuzzy SR matrix) generated by using an order invariant membership function. The clustering property is the essential property of FZT, and is exploited (through the re suiting fuzzy samples and fuzzy ranks) in two image denoising applications, namely, DCT coded image deblocking and impulsive noise elimination. Our proposed methods demonstrate superior performance than the conventional methods in all the simulations, showing that FZT is a powerful tool for image processing.

Keywords

discrete cosine transforms; image denoising; impulse noise; interference suppression; transform coding; DCT coded image deblocking; clustering property; data-adaptive nonlinear transformation; fuzzy application; fuzzy rank; fuzzy sample; fuzzy transformation theory; image denoising; image processing; impulsive noise elimination; order invariant membership function; spatial-rank matrix; transformation matrix; Application software; Discrete cosine transforms; Distribution functions; Filtering theory; Filters; Fuzzy sets; Image processing; Smoothing methods; Statistics; Strontium;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on

ISSN

1522-4880

Print_ISBN

0-7803-7750-8

Type

conf

DOI

10.1109/ICIP.2003.1247107

Filename

1247107