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Compressed sensing image reconstruction based on Gaussian scale mixtures model
Author(s): 
Pages: 432-438
Year: Issue:  3
Journal: Optical Technique

Abstract: 在图像处理领域中,压缩传感重构是稀疏表示下的最重要的病态反问题之一.压缩传感图像重构利用图像可稀疏表示的先验知识,从比奈奎斯特采样率低得多的随机投影观测值中重构原始图像.为了克服传统的压缩传感算法中收敛速度慢和未利用变换系数的邻域统计特性的缺点,提出了基于高斯混合尺度模型的压缩传感图像重构算法,证明了独立的高斯混合尺度分布作为压缩传感重构的稀疏先验知识的可行性,结合全变差调整进一步提高算法的性能....
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