A New Fuzzy Logic Image De-noising Algorithm Based on Gradient Detection

Author

Tang, Liangrui ; Wang, Hongting ; Qi, Bing

Author_Institution

North China Electr. Power Univ., Beijing

Volume

2

fYear

2007

fDate

24-27 Aug. 2007

Firstpage

103

Lastpage

107

Abstract

This paper presents a gradient detecting fuzzy logic-based algorithm (GDFF) for image de-nosing issue. For the first step, GDFF selects different fixed filtering sub-windows to process the input signal by linear de-noising. And then it modifies the de-noised results by a set of membership functions established by making full use of edge information. Finally, these signals are summed with weight to accomplish the image de-noising. Experiments illustrate that, GDFF performs a better de-noising effect with PSNR Gain 2.65-10.34 dB compared with WFM and FIRE, when noise probability exceeds from 0.5 to 0.8. Furthermore, GDFF exhibits more effective performance both in reserving image edge and in removing noise.

Keywords

filtering theory; fuzzy set theory; gradient methods; image denoising; edge information; fuzzy logic image denoising algorithm; gradient detecting fuzzy logic-based algorithm; linear denoising; noise probability; subwindows filtering; Filtering; Fires; Fuzzy logic; Image denoising; Image edge detection; Noise reduction; Nonlinear filters; PSNR; Performance gain; Signal processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on

Conference_Location

Haikou

Print_ISBN

978-0-7695-2874-8

Type

conf

DOI

10.1109/FSKD.2007.77

Filename

4406054