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Low complexity joint source-channel decoding for transmission of wavelet compressed images

机译:低复杂度的联合源信道解码,用于小波压缩图像的传输

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摘要

To utilize residual redundancy to reduce the error induced by fading channels and decrease the complexity of the field model to describe the probability structure for residual redundancy, a simplified statistical model for residual redundancy and a low complexity joint source-channel decoding(JSCD) algorithm are proposed. The complicated residual redundancy in wavelet compressed images is decomposed into several independent 1 -D probability check equations composed of Markov chains and it is regarded as a natural channel code with a structure similar to the low density parity check (LDPC) code. A parallel sum-product (SP) and iterative JSCD algorithm is proposed. Simulation results show that the proposed JSCD algorithm can make full use of residual redundancy in different directions to correct errors and improve the peak signal noise ratio (PSNR) of the reconstructed image and reduce the complexity and delay of JSCD. The performance of JSCD is more robust than the traditional separated encoding system with arithmetic coding in the same data rate.
机译:为了利用剩余冗余减少信道衰落引起的误差并降低描述剩余冗余概率结构的场模型的复杂度,提出了一种简化的剩余冗余统计模型和低复杂度联合源信道解码(JSCD)算法。建议。小波压缩图像中复杂的剩余冗余被分解为由马尔可夫链组成的几个独立的一维概率校验方程,被视为具有类似于低密度奇偶校验(LDPC)码的结构的自然信道码。提出了并行求和(SP)和迭代JSCD算法。仿真结果表明,所提出的JSCD算法可以充分利用不同方向的剩余冗余来纠正错误,提高重建图像的峰值信噪比,降低JSCD的复杂度和延迟。 JSCD的性能比在相同数据速率下使用算术编码的传统分离编码系统更强大。

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