首页> 外文期刊>Signal processing >A tutorial overview on the properties of the discrete cosine transform for encoded image and video processing
【24h】

A tutorial overview on the properties of the discrete cosine transform for encoded image and video processing

机译:有关编码图像和视频处理的离散余弦变换的属性的教程概述

获取原文
获取原文并翻译 | 示例

摘要

Discrete trigonometric transforms, such as the discrete cosine transform (DCT) and the discrete sine transform (DST), have been extensively used in signal processing for transform-based coding. The even type-II DCT, used in image and video coding, became specially popular to decorrelate the pixel data and minimize the spatial redundancy. Albeit this DCT tends to be the most often used, it integrates a broader family of transforms composed of eight DCTs and eight DSTs. However, even though most applications require little knowledge more than the actual DCT definition and its inverse, it is often widely regarded that the implementation of more complex operations on transformed data sequences (transcoding) requires a more in-depth knowledge about its precise definitions and formal mathematical properties. One of such relations is the multiplication-convolution property, often required to implement more specific and complex manipulations. Considering that such information is still spread into several documents and manuscripts, the main purpose of this article is to provide a broad set of practical and useful information in a single and self-contained source, embracing a wide range of definitions and properties related to the DCT and DST families, with a special emphasis on its application to image and video processing.
机译:离散三角变换,例如离散余弦变换(DCT)和离散正弦变换(DST),已广泛用于基于变换的编码的信号处理中。在图像和视频编码中使用的偶数II型DCT变得特别流行,用于去相关像素数据并最小化空间冗余。尽管该DCT往往是最常用的,但它集成了由8个DCT和8个DST组成的更广泛的转换系列。但是,即使大多数应用程序比实际的DCT定义及其逆要求仅需要很少的知识,但通常人们普遍认为,对转换后的数据序列执行更复杂的操作(代码转换)需要对其精确定义和操作更深入的了解。正式的数学性质。这种关系之一是乘法-卷积属性,通常需要使用乘法-卷积来实现更具体和复杂的操作。考虑到此类信息仍散布在多个文档和手稿中,因此本文的主要目的是在单一且独立的来源中提供广泛的实用和有用的信息,其中包含与产品相关的各种定义和属性。 DCT和DST系列,特别强调其在图像和视频处理中的应用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号