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Efficient Rate–Distortion Optimal Packetization of Embedded Bitstreams Into Independent Source Packets

机译:嵌入式比特流到独立源数据包的高效速率失真优化打包

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This paper addresses the rate-distortion (R-D) optimal packetization (RDOP) of embedded bitstreams into independent source packets, in order to limit error propagation in transmission of images over packet noisy channels. The input embedded stream is assumed to be an interleaving of K independently decodable basic streams. To form N (N <; K) independent source packets, the set of basic streams is partitioned into N groups. The streams within each group are then interleaved to generate a source packet. Error/erasure protection may be further applied along/across source packets, to produce the channel packets to be transmitted. The RDOP problem previously formulated by Wu et at. has the goal of finding the partitioning that minimizes the distortion when all source packets are decoded. We extend the problem formulation such that to also include the minimization of the expected distortion for general transmission scenarios that may apply uneven erasure/ error protection. Further, we show that the dynamic programming (DP) algorithm of Wu et al. can be extended to solve the general RDOP problem. The main contribution of this paper is a fast divide-and-conquer algorithm (D&C) to find the globally optimal solution, under the assumption that all basic streams have convex R-D curves. Instrumental in obtaining the fast solution is our result which proves that the problem can be formulated as a series of matrix search problems in totally monotone matrices. The proposed D&C reduces the running time from O(K2 LN) where L is the size of each packet achieved by the DP solution to O(NKL log K). Experiments on SPIHT coded images demonstrate that the speedup is significant in practice.
机译:本文将嵌入式比特流的速率失真(R-D)最佳打包(RDOP)分解为独立的源数据包,以限制在数据包有噪声通道上传输图像时的错误传播。假定输入的嵌入式流是K个可独立解码的基本流的交织。为了形成N(N <; K)个独立的源数据包,基本流集被划分为N个组。然后将每个组中的流进行交织以生成源数据包。可以沿着/跨源分组进一步应用错误/擦除保护,以产生要发送的信道分组。 Wu等人先前提出的RDOP问题。目的是找到在对所有源分组进行解码时将失真最小化的分区。我们扩展问题的表述方式,使其也包括对可能应用不均匀擦除/错误保护的一般传输方案的预期失真的最小化。此外,我们证明了Wu等人的动态规划(DP)算法。可以扩展以解决一般的RDOP问题。本文的主要贡献是在所有基本流都具有凸R-D曲线的假设下,一种快速分治算法(D&C),它可以找到全局最优解。我们的结果有助于获得快速解,这证明该问题可以表示为完全单调矩阵中的一系列矩阵搜索问题。提出的D&C将运行时间从O(K 2 LN)减少,其中L是DP解决方案达到O(NKL log K)的每个数据包的大小。在SPIHT编码图像上进行的实验表明,加速实际上是很重要的。

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