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A compressive domain saliency-based adaptive measurement method for image recovery

机译:基于压缩域显着的图像恢复自适应测量方法

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This paper proposes an image compressed sensing method by adaptive measurement matrix based on saliency detection in the compressive domain. The saliency mapping algorithm is simply the difference between adjacent compressive measurements of neighboring image patches. The adjustment algorithm of subsampling rate is a multi - group approximation by sorting and clustering. It is verified by simulation experiments that the proposed method has higher reconstruction quality than the classical methods with fixed measurement matrices.
机译:本文提出了一种基于压缩域中显着性检测的自适应测量矩阵的图像压缩检测方法。显着的映射算法仅仅是相邻图像斑块的相邻压缩测量的差异。通过对分类和聚类来调整算法是一种多组近似。通过仿真实验验证,提出的方法与具有固定测量矩阵的经典方法具有更高的重建质量。

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