Multiple Description Image Coding Based on Compression-Guided Optimization

Shuyuan Zhu, Zhiying He, Xiandong Meng, Guanghui Liu, B. Zeng
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Abstract

In this paper, we design a new multiple description coding scheme for image signals based on our proposed compression-guided optimization. Firstly, we propose a compression-constrained adaptive filtering method to produce two descriptions for the source image, where the proposed filtering algorithm works not only to guarantee a high-quality side decoding but also make a high-efficient central decoding. Secondly, we design a compression-dependent deblocking algorithm based on the transform coefficients which are decoded from both descriptions to improve the performance for the cental decoding. Experimental results demonstrate that our proposed method achieves impressive performance gains when it is applied to image signals.
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基于压缩导向优化的多描述图像编码
在本文中,我们基于提出的压缩导向优化设计了一种新的图像信号多重描述编码方案。首先,我们提出了一种压缩约束的自适应滤波方法,对源图像产生两个描述,其中所提出的滤波算法既保证了高质量的侧解码,又保证了高效的中心解码。其次,我们设计了一种基于变换系数的压缩相关的去块算法,以提高中心解码的性能。实验结果表明,将该方法应用于图像信号时,取得了令人印象深刻的性能提升。
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