@inproceedings{842373b375ba4de8bfc55ecd9709357a,
title = "L1/2-constrained morphological component analysis",
abstract = "In this paper, we introduce the l1/2 constraint into the morphological component analysis (MCA) to solve the problem of cartoon and texture separation, inpainting and super-resolution for images. The newly proposed iterative half thresholding algorithm is recast in an analysis formulation, and can be well embedded in the MCA framework. Other constraint, such as total variation (TV), can also be combined to enhance the restoration of this modified MCA method. The superiority of the proposed l1/2- constrained MCA method is demonstrated by experimental results.",
keywords = "Compressive sensing, image inpainting, l regularization, morphological component analysis (MCA), sparse representation, superres-olution",
author = "Pengliang Yang and Jinghuai Gao and Wenchao Chen",
year = "2013",
doi = "10.1109/ChinaSIP.2013.6625298",
language = "英语",
isbn = "9781479910434",
series = "2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings",
pages = "63--66",
booktitle = "2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings",
note = "2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 ; Conference date: 06-07-2013 Through 10-07-2013",
}