Lossless Video Compression Using Bayesian Networks and Entropy Coding

被引：0

作者：

Venkat, Rochan Avlur ^{[1
]}

Vaidyanathan, Chandrasekar ^{[2
]}

机构：

[1] Mahindra Ecole Cent, Comp Sci & Engn, Hyderabad, India

[2] Dayanand Sagar Univ, Dept Math, Bangalore, Karnataka, India

来源：

PROCEEDINGS OF 2019 IEEE REGION 10 SYMPOSIUM (TENSYMP) | 2019年

关键词：

Bayesian Network; Entropy Coding; Lossless Compression; Video Compression; Video Coding Algorithms; Encoder; Decoder;

D O I：

10.1109/tensymp46218.2019.8971209

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Lossless video compression algorithms are used in applications ranging from archival of video records to the field of medicine. In this paper, we propose a simple yet effective encoding technique for lossless video compression. Our technique automatically learns Bayesian Networks to discover Conditional Dependencies in a video stream through Stochastic Hill Climbing. Utilizing this network, variable length codes are generated using Entropy Coding procedure achieved by Huffman Coding. This structured data is used to encode the video stream. The algorithm has been tested and compared alongside H.264, FF Video Codec 1 (FFVI) and Gzip. The proposed compression model performs on average at least as good and at times better than the aforementioned techniques.

引用

页码：254 / 259

页数：6