A Fast NL Means De-noise Algorithm Based on Fuzzy Adaptive

In order to overcome the large computing of Non-Local (NL) means for image de-noise, a new method of FANL(Fuzzy Adaptive Non Local) means de-noise is proposed in this paper. It is proposed that the noise variance is estimated from noise image. And the optimism parameter is estimated by variance and noise image standard deviation. The optimism parameter is acquired from fuzzy control algorithm to a better de-noise effect and high peak signal to noise ratio (PSNR). Experimental results show that the proposed algorithm is effective and comparing favorable with existing techniques, Practical application shows that this method also proposes a reliable parameter estimation method, and the result is reliable to stitching a large image. At the same time, the processing time is faster than NL means method.