Image Restoration Using Hybrid Features Improvement on Morphological Component Analysis |
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Authors: | Der-Chang Tseng Ru-Yin Wei Ching-Ta Lu Ling-Ling Wang |
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Affiliation: | 1. Department of Electronic Engineering, National Taipei University of Technology, Taipei, 10608;2. Quanta Computer Inc., Taipei, 11167;3. Department of Information Communication, Asia University, Taichung, 41354 |
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Abstract: | Images are generally corrupted by impulse noise during acquisition and transmission. Noise deteriorates the quality of images. To remove corruption noise, we propose a hybrid approach to restoring a random noise-corrupted image, including a block matching 3D (BM3D) method, an adaptive non-local mean (ANLM) scheme, and the K-singular value decomposition (K-SVD) algorithm. In the proposed method, we employ the morphological component analysis (MCA) to decompose an image into the texture, structure, and edge parts. Then, the BM3D method, ANLM scheme, and K-SVD algorithm are utilized to eliminate noise in the texture, structure, and edge parts of the image, respectively. Experimental results show that the proposed approach can effectively remove interference random noise in different parts; meanwhile, the deteriorated image is able to be reconstructed well. |
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Keywords: | Adaptive non-local mean (ANLM) block matching 3D (BM3D) image restoration morphological component analysis (MCA) singular value decomposition (SVD) |
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