A group matching pursuit for image reconstruction
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- 作者：Wan Lia ; b ; liwan0_0@163.com" class="auth_mail" title="E-mail the corresponding author ; Fang Liua ; b ; f63liu@163.com" class="auth_mail" title="E-mail the corresponding author ; Licheng Jiaob ; Hongxia Haoa ; b ; Shuyuan Yangb
- 关键词：Compressive sensing ; Group matching pursuit ; Neighborhood structures ; Wavelet transform
- 刊名：Signal Processing: Image Communication
- 出版年：2016
- 出版时间：November 2016
- 年：2016
- 卷：49
- 期：Complete
- 页码：47-62
- 全文大小：6263 K
文摘
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GMP improved the reconstruction result with the aggregation of the wavelet domain.
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With the group correlation value, GMP can accurately locate the position of large coefficients.
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The estimated image edge is used to guide the locations of significant coefficients.
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The group coefficients are modeled by a multivariate Gaussian distribution and solved by MAP estimate.