An Efficient Solution for Video Compression Using an Original Modified Algorithm Applied to Improve the 3D Discrete Cosine Transform

R. Radescu
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引用次数: 3

Abstract

The 3D-DCT is used in video compression when the applied basic principle is the correlation between adjacent pixels in a frame and the correlation between pixels from the same position in adjacent frames (temporal correlation). This principle uses the concept that a video sequence can be seen as a parallelepiped representing the entire video sequence, divided into smaller, independently encoded parallelepipeds, the most commonly format being a "video cube" of 8×8×8 size. When passing this cube through the 3D-DCT algorithm that applies to it, the corresponding quantization tables must be known by both the encoder and the decoder to be able to decompress the video information. This paper presents an original method of implementing a modified 3D-DCT compression algorithm, which is a variant derived from it and which brings certain improvements to the standard algorithm. The main improvement is to replace fixed-sized "video cubes" by creating variable-length parallelepipeds over time, giving up the fixed value of 8 for the "video cube" dimension, which means considerable reductions in the volume of this parallelepiped when its sides are smaller than 8. n-bit operations can be performed more efficiently and resource-saving when n < 8 and implicitly the value of 2n – 1 no longer complies with the divisibility by 8. Other improvements are related to how the information bits are saved when storing them in the compressed video file. Reading from this file and writing in this file run in large blocks, to avoid accessing the file too often with short readings or writings. The design and implementation details, as well as the analysis of the compression performance obtained (including the consumption of time divided by type of function used) are thoroughly presented in the paper.
一种改进三维离散余弦变换的原始改进算法在视频压缩中的应用
3D-DCT用于视频压缩,其应用的基本原理是一帧中相邻像素之间的相关性和相邻帧中相同位置的像素之间的相关性(时间相关性)。这个原理使用的概念是,视频序列可以看作是一个平行六面体,代表整个视频序列,分成更小的,独立编码的平行六面体,最常见的格式是8×8×8大小的“视频立方体”。当通过应用于该立方体的3D-DCT算法传递该立方体时,编码器和解码器都必须知道相应的量化表,才能对视频信息进行解压缩。本文提出了一种改进的3D-DCT压缩算法的原始实现方法,该算法是在其基础上衍生的一种变体,对标准算法进行了一定的改进。主要的改进是,随着时间的推移,通过创建可变长度的平行六面体来取代固定大小的“视频立方体”,放弃“视频立方体”维度的固定值8,这意味着当平行六面体的边长小于8时,其体积会大幅减少。当n < 8且2n - 1的隐式值不再符合8的可整除性时,可以更高效地执行n位运算,节省资源。其他改进与在压缩视频文件中存储信息位时如何保存有关。从该文件读取和写入该文件以大块运行,以避免过于频繁地使用简短的读取或写入操作访问该文件。文中详细介绍了设计和实现的细节,并对所获得的压缩性能进行了分析(包括按所使用的函数类型划分的时间消耗)。
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