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Rate-distortion methods for image and video compression

机译:图像和视频压缩的速率失真方法

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In this article we provide an overview of rate-distortion (R-D) based optimization techniques and their practical application to image and video coding. We begin with a short discussion of classical rate-distortion theory and then we show how in many practical coding scenarios, such as in standards-compliant coding environments, resource allocation can be put in an R-D framework. We then introduce two popular techniques for resource allocation, namely, Lagrangian optimization and dynamic programming. After a discussion of these techniques as well as some of their extensions, we conclude with a quick review of literature in these areas citing a number of applications related to image and video compression and transmission.
机译:在本文中,我们概述了基于速率失真(R-D)的优化技术及其在图像和视频编码中的实际应用。我们首先简短讨论经典的速率失真理论,然后说明在许多实际的编码方案中,例如在符合标准的编码环境中,如何将资源分配放入R-D框架中。然后,我们介绍两种流行的资源分配技术,即拉格朗日优化和动态规划。在讨论了这些技术及其扩展之后,我们以对这些领域的文献的快速回顾作为结尾,并列举了许多与图像和视频压缩与传输相关的应用。

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