A New Fuzzy Logic Image De-noising Algorithm Based on Gradient Detection
Liangrui Tang, Hongting Wang, Bing Qi · 2007
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.