首页 | 本学科首页   官方微博 | 高级检索  
     


A fast VQ codebook search with initialization and search order
Authors:Chin-Chen Chang  Yi-Pei Hsieh
Affiliation:1. School of Management and Engineering, Nanjing University, Nanjing 210093, China;2. School of Finance, Nanjing University of Finance and Economics, Nanjing 210046, China;3. Graduate School of Information, Production and Systems, Waseda University, Kitakyushu 808-0135, Japan;1. College of Environmental Science and Engineering, State Environmental Protection Engineering Center for Pollution Treatment and Control in Textile Industry, Donghua University, Shanghai 201620, China;2. Department of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, China;1. School of Electronic Engineering, Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi’an, China;2. Department of Computer Science and Software Engineering, Swinburne University of Technology, Melbourne, Australia
Abstract:Vector quantization (VQ), a lossy image compression, is widely used for many applications due to its simple architecture, fast decoding ability, and high compression rate. Traditionally, VQ applies the full search algorithm to search for the codeword that best matches each image vector in the encoding procedure. However, matching in this manner consumes a lot of computation time and leads to a heavy burden for the VQ method. Therefore, Torres and Huguet proposed a double test algorithm to improve the matching efficiency. However, their scheme does not include an initiation strategy to choose an initially searched codeword for each image vector, and, as a result, matching efficiency may be affected significantly. To overcome this drawback, we propose an improved double test scheme with a fine initialization as well as a suitable search order. Our experimental results indicate that the computation time of the double test algorithm can be significantly reduced by the proposed method. In addition, the proposed method is more flexible than existing schemes.
Keywords:
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号