Title :
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
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;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
DOI :
10.1109/FSKD.2007.77
