A noise-ranking switching filter for images with general fixed-value impulse noises

作者：Chou Hsien Hsin; Hsu Ling Yuan^*

来源：Signal Processing, 2015, 106: 198-208.

DOI：10.1016/j.sigpro.2014.07.015

• Switching filter
• General fixed-value impulsive noise
• Noise ranking

Impulse noise is generally classified into random-value and fixed-value types. However, most of the previous literatures recognized salt and pepper (S&P) noise as the fixed-value impulse noise because it is easily detected and recovered. This article studies a general fixed-value impulse noise in which the corrupted pixels are set to not only the minimum-maximum values but also any fixed intensities. A novel noise-ranking switching filter (NRSF) is proposed for suppressing these tough noise types. In order to clearly distinguish the noise-free pixels from noisy pixels having the same gray value, the detection stage of NRSF consists of three modified methodologies, named global-local statistics analysis, sectional boundary discriminative noise detection, and a directional test. Once a corrupted pixel has been identified, the same matrix convolution technique used in the last test is employed again in the second NRSF stage to recover the noise. Additionally, it is suggested that the corrupted pixels are processed via the rank of noise density for improving the suppression capability at very high noise ratio. Although the NRSF is driven for a new impulse noise model, it outperforms several state-of-the-art algorithms in terms of noise suppression and detail preservation even for images with the traditional S&P noise.

• 出版日期2015-1