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Image compression-based multiple description transform coding using NSCT and OMP approximation

机译:使用NSCT和OMP逼近的基于图像压缩的多描述变换编码

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摘要

In this paper, we present a novel multiple description transform image coding architecture, which uses an attractive transform called non-subsampled contourlet transform (NSCT). It combines NSCT and orthogonal matching pursuit algorithm (OMP) to give a sparse representation of images, aiming at solving the compression problem due to the redundancy property of NSCT. In this way, OMP turns to give a solution to remove the redundancies. We evaluate the performance of our image coder in the case of four descriptions that are dispatched over different channels. The experimentations show that the proposed method is efficient and the potential using NSCT than DWT in multiple description image coding, is evaluated by PSNR in each case of packet loss, where every description can reconstruct the image with acceptable fidelity, the later is much better if all descriptions are available.
机译:在本文中,我们提出了一种新颖的多描述变换图像编码体系结构,该体系结构使用了一种有吸引力的变换,称为非下采样轮廓波变换(NSCT)。它结合了NSCT和正交匹配追踪算法(OMP)来给出图像的稀疏表示,旨在解决由于NSCT的冗余特性而引起的压缩问题。这样,OMP就提供了消除冗余的解决方案。在通过不同渠道分发的四个描述的情况下,我们评估图像编码器的性能。实验表明,所提出的方法是有效的,在丢包的每种情况下,通过PSNR评估在多描述图像编码中使用NSCT而不是DWT的潜力,其中每个描述都可以以可接受的保真度重建图像,如果所有描述均可用。

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