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A Novel Multi-level Wavelet Image Coding Algorithm by Full Sub-band Compressed Sensing

机译:全子带压缩检测的新型多级小波图像编码算法

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The performance of wavelet transform based image compressed sensing coding algorithms severely rely on the level of wavelet transform. To this end, this paper investigated the combination of multi-level wavelet full sub-band in compressed sensing framework. Firstly, we constructed a full sub-band coefficient sparse vector of multi-level discrete wavelet transform. Secondly, we designed a weight matrix to improve measurement matrix. Finally, sparsity vector was processed by compressed sensing to get the measured value. Compared with the exiting algorithms, the experimental results of the proposed algorithm show that the PSNRs of reconstructed images is improve up to I~2dB under the same objective quality.
机译:基于小波变换的图像压缩检测编码算法的性能严重地依赖于小波变换级别。为此,本文研究了压缩传感框架中的多级小波完整子带的组合。首先,我们构建了一个全子带系数稀疏向量的多级离散小波变换。其次,我们设计了一种重量矩阵来改善测量矩阵。最后,通过压缩感测处理稀疏载体以获得测量值。与退出算法相比,所提出的算法的实验结果表明,重建图像的PSNR在相同的客观质量下改善到I〜2dB。

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