Elsevier

Digital Signal Processing

Volume 22, Issue 6, December 2012, Pages 903-912
Digital Signal Processing

Improved bilateral filter for suppressing mixed noise in color images

https://doi.org/10.1016/j.dsp.2012.06.012Get rights and content

Abstract

It is a challenging problem to suppress mixed noise in color images. The traditional bilateral filter can excellently reduce additive noise without destroying image edges and details, but it fails to remove impulsive noise. This paper presents an improved bilateral filtering method, which can simultaneously suppress both impulsive and additive noise. The proposed solution first introduces a new weighting function to the bilateral filtering mechanism, which is experimentally more effective than the traditional Gaussian kernel. Then, either the current pixel or the vector median, instead of always the current pixel itself, is chosen as the base to take part in the bilateral filtering action, which is determined by whether the current pixel is a possible impulse or not. The experimental results show that the proposed solution can simultaneously remove impulsive and additive noise while preserving edge structures, and outperforms other vector filtering methods in terms of both objective evaluation and subjectively visual quality.

Section snippets

Lianghai Jin received the BS and MS degrees in computer science from Central South University (China) in 1988 and Beijing Jiaotong University (China) in 2002, and the PhD degree in pattern recognition and intelligent systems from Huazhong University of Science and Technology (China) in 2008, where he is now an associate professor with the School of Computer Science and Technology. From 1988 to 1999, he was with a Railway Institute in China as an engineer and senior engineer, respectively. His

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  • Cited by (0)

    Lianghai Jin received the BS and MS degrees in computer science from Central South University (China) in 1988 and Beijing Jiaotong University (China) in 2002, and the PhD degree in pattern recognition and intelligent systems from Huazhong University of Science and Technology (China) in 2008, where he is now an associate professor with the School of Computer Science and Technology. From 1988 to 1999, he was with a Railway Institute in China as an engineer and senior engineer, respectively. His research interests include color and video image processing.

    Caiquan Xiong received the BS degree in information engineering from the Communication University of China in 1988, MS degree in computer science in 2001 and the PhD degree in pattern recognition and intelligent systems from Huazhong University of Science and Technology (China) in 2008. He is now a professor with Hubei University of Technology (China). His research interests include non-monotonic reasoning, pattern recognition and artificial intelligence.

    Hong Liu received the BS and MS degrees in optoelectronic engineering and computer science from Huazhong University of Science and Technology (China) in 1984 and 1995, respectively, and the PhD degree in electronic engineering from Teesside University (United Kingdom) in 2000. She is currently an associate professor with the School of Computer Science and Technology, Huazhong University of Science and Technology. Her research interests include image processing and computer networking.

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