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

机译:一种基于压缩域显着性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:提出了一种基于压缩域显着性检测的自适应测量矩阵图像压缩感知方法。显着性映射算法只是相邻图像块的相邻压缩测量之间的差异。二次采样率的调整算法是通过排序和聚类进行的多组近似。仿真实验证明,该方法比固定测量矩阵的经典方法具有更高的重建质量。

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