Adaptive filtering algorithm for mixed noise image based on wavelet transform

zhang libao; ao pengliang

Volume 22 Issue 11

Sep. 2010

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Article Navigation > High Power Laser and Particle Beams > 2010 > 22(11): 0-

guo linhui, gao songxin, wu deyong, et al. Beam collimation of diode laser vertical stack[J]. High Power Laser and Particle Beams, 2011, 23.

Citation:

zhang libao, ao pengliang. Adaptive filtering algorithm for mixed noise image based on wavelet transform[J]. High Power Laser and Particle Beams, 2010, 22.

guo linhui, gao songxin, wu deyong, et al. Beam collimation of diode laser vertical stack[J]. High Power Laser and Particle Beams, 2011, 23.

Citation:

zhang libao, ao pengliang. Adaptive filtering algorithm for mixed noise image based on wavelet transform[J]. High Power Laser and Particle Beams, 2010, 22.

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Adaptive filtering algorithm for mixed noise image based on wavelet transform

zhang libao^1,2,
ao pengliang¹

1.
College of Information Science and Technology,Beijing Normal University,Beijing 100875,China;
2.
State Key Laboratory of Remote Sensing Science,Beijing Normal University,Beijing 100875,China

Publish Date: 2010-09-29

Abstract

Abstract

To filter out salt and pepper noise and Gaussian noise, this paper presents a waveletbased adaptive filtering algorithm for mixed noise. The median filter is firstly applied to remove salt and pepper noise and the edge detection is used to distinguish between the nonedge region and the edge region. Then an improved average filter is adopted on the nonedge region, initially weakening the Gaussian noise, without blurring the edge. Finally, an improved wavelet threshold filtering algorithm is utilized on the entire image, using different threshold functions on different subbands. The parameters of these threshold functions are gained in a linear regression process. The experimental results show that the proposed adaptive mixednoise filtering algorithm can effectively remove salt and
- image processing,
- image denoising,
- edge detection,
- wavelet transform

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