Image denoising using 2-D FIR filters designed with DEPSO

  • Authors:

  • Jingyu Hua;Wangkun Kuang;Zheng Gao;Limin Meng;Zhijiang Xu

  • Affiliations:

  • College of Information Engineering, Zhejiang University of Technology, Hangzhou, China 310023 and National Mobile Communications Research Laboratory, Southeast University, Nanjing, China 210096;College of Information Engineering, Zhejiang University of Technology, Hangzhou, China 310023;College of Information Engineering, Zhejiang University of Technology, Hangzhou, China 310023;College of Information Engineering, Zhejiang University of Technology, Hangzhou, China 310023;College of Information Engineering, Zhejiang University of Technology, Hangzhou, China 310023

  • Venue:
  • Multimedia Tools and Applications
  • Year:
  • 2014

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Abstract

Digital images are often corrupted by additive noises during transmission. Thus, how to alleviate noise as much as possible has received concerns for decades. In this paper, we present a simple denoising method based on two dimensional (2-D) finite impulse response (FIR) filtering, where by differential evolution particle swarm optimization (DEPSO) algorithm, five two dimensional finite impulse response filters are designed to filter different kinds of pixels. Comprised by differential evolution algorithm and particle swarm optimization algorithm, differential evolution particle swarm optimization algorithm is effective and robust, which helps to yield better denoise performance. And computer simulation demonstrates that the proposed method is superior to the conventional lowpass filtering method, as well as the modern bilateral filtering and stochastic denoising method.