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Multiple Description Image Coding Based on Delta-Sigma Quantization With Rate-Distortion Optimization

机译:基于Delta-Sigma量化和速率失真优化的多描述图像编码

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摘要

Recently, Østergaard and Zamir revealed the connection between multiple description coding and delta-sigma quantization (DSQ). The principle has been applied to image coding, with main focus on the framework where each block is processed separately. In this brief, we propose a two-channel multiple description image coding scheme that performs inter-block processing. The source image is first rearranged into a block sequence. Then, vector DSQ is performed with a bank of noise-shaping filters. Their coefficients as well as the quantization steps are chosen by a rate-distortion optimization algorithm. A post-processing algorithm is proposed for side decoding. Experiment results show the improvement achieved by the proposed scheme in terms of both peak signal-to-noise ratio values and subjective quality.
机译:最近,Østergaard和Zamir揭示了多描述编码和delta-sigma量化(DSQ)之间的联系。该原理已经应用于图像编码,主要集中在单独处理每个块的框架上。在本摘要中,我们提出了一种执行块间处理的两通道多描述图像编码方案。首先将源图像重新排列为块序列。然后,使用一组噪声整形滤波器执行矢量DSQ。它们的系数以及量化步长由速率失真优化算法选择。提出了一种用于边解码的后处理算法。实验结果表明,该方案在峰值信噪比值和主观质量方面均实现了改进。

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