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.
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This work was supported by the key project of Chinese ministry of education under grant No.210087, Zhejiang provincial science & technology project (No.2012R10011-6) and in part by the open research fund of national mobile communications research laboratory, Southeast University (No.2010D06).
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Hua, J., Kuang, W., Gao, Z. et al. Image denoising using 2-D FIR filters designed with DEPSO. Multimed Tools Appl 69, 157–169 (2014). https://doi.org/10.1007/s11042-012-1263-1
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DOI: https://doi.org/10.1007/s11042-012-1263-1