Abstract
Image restorations with sparse representation theory have drawn considerable interest in recent years. In this paper, considering the inter-pixel relationship among the R, G and B planes, we extend the joint sparse model to restore the color images. The objective is to achieve the colors of the restored images more natural than that of the reconstructing results with the method by restoring different color planes individually. In experimental section, the extended joint sparse model is applied to restore the corrupted color images by additive Gaussian noise and the color images with missing pixels. Four common used color images are used to test the effectiveness of the novel color image sparse model based image restoration. The results clearly indicate the feasibility of the proposed approach.
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Luo, J., Yang, B., Chen, Z. (2012). Color Image Restoration via Extended Joint Sparse Model. In: Liu, CL., Zhang, C., Wang, L. (eds) Pattern Recognition. CCPR 2012. Communications in Computer and Information Science, vol 321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33506-8_61
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DOI: https://doi.org/10.1007/978-3-642-33506-8_61
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33505-1
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