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An image representation scheme by hybrid compressive sensing

机译:混合压缩感知的图像表示方案

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摘要

Compressive sensing based image compression is a new paradigm shift in image representation and coding. The existing CS based image compression schemes are based on sparsity of the signals in transform domain. In this paper multiscale DWT is applied for sparse representation of the image. Instead of directly taking the measurements on sparse representation, statistical properties of low and high frequency subbands are studied. Based on the statistical properties of high and low band coefficients, a hybrid encoding scheme is proposed to encode low and high frequency subbands differently. At the decoder side, the combined bit stream is separated, and by fully exploiting the intra and inter scale correlation of multiscale DWT, different recovery algorithms are developed for low frequency and high frequency sub bands.
机译:基于压缩的感测的图像压缩是图像表示和编码的新范式偏移。现有的基于CS的图像压缩方案基于变换域中的信号的稀疏性。在本文中,Multiscale DWT用于图像的稀疏表示。而不是直接考虑稀疏表示的测量,研究了低频和高频子带的统计特性。基于高频带系数的统计特性,提出了一种不同地编码低频和高频子带的混合编码方案。在解码器侧,分离组合的比特流,并且通过充分利用MultiScale DWT的帧内和互相相关,为低频和高频子带开发了不同的恢复算法。

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