Image Denoising Using FIR Filters Designed with Evolution Strategies

Images are often corrupted by noise due to various factors during their acquisition and transmission phases. Image denoising is aimed to remove the noise as well as preserving image features as much as possible. This paper presents an adaptive image denosing method using FIR (finite impulse response) filters. The FIR filter coefficients are optimized by using evolution strategies algorithm in which the FIR coefficients are evolved through crossover and mutation operations. Simulations demonstrate that it can efficiently remove the noise, and thus, significantly improve the visual quality of the degraded image. In terms of PSNR, it outperforms the comparable methods considered in the simulations.