Salt and pepper noise removal in binary images using image block prior probabilities |
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| Affiliation: | 1. School of Information Science and Technology, Sun Yat-sen University, Guangzhou 510006, China;2. School of Software, Sun Yat-sen University, Guangzhou 510006, China;1. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;2. School of Computer Science and Engineering, Hunan University of Science and Technology, China;3. Institute of Information Engineering, Chinese Academy of Sciences, National Engineering Laboratory for Information Security Technologies, Beijing, China;4. Department of Computer, Shandong University, Weihai, China;1. LAboratoire du Traitement du Signal et de l’Image (LATSI), Department of Electronic, Faculty of Technology, University Saad Dahlab of Blida, Algeria;2. ICUBE, Laboratoire des Sciences de l’Ingénieur, de l’Informatique et de l’Imagerie, University of Strasbourg, E.Phot Group, France |
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| Abstract: | During scanning and transmission, images can be corrupted by salt and pepper noise, which negatively affects the quality of subsequent graphic vectorization or text recognition. In this paper, we present a new algorithm for salt and pepper noise suppression in binary images. The algorithm consists of the computation of block prior probabilities from training noise-free images; noise level estimation; and the maximum a posteriori probability estimation of each image block. Our experiments show that the proposed method performs significantly better than the state of the art techniques. |
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| Keywords: | Salt and pepper noise Image denoising Binary images Bayesian inference Training methods Impulse noise Image restoration Image filtering |
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