@article{6644a3d6f51a41cfaf6859395d27180b,
title = "Combined Techniques Of Singular Value Decomposition and Vector Quantization For Image Coding",
abstract = "The combination of singular value decomposition (SVD) and vector quantization (VQ) is proposed as a compression technique to achieve low bit rate and high quality image coding. Given a codebook consisting of singular vectors, two algorithms, which find the best-fit candidates without involving the complicated SVD computation, are described. Simulation results show that the proposed methods are better than the discrete cosine transform (DCT) in terms of energy compaction, data rate, image quality, and decoding complexity.",
author = "Yang, {Jar Ferr} and Lu, {Chiou Liang}",
note = "Funding Information: Manuscript received October 22, 1992; revised October 18, 1994. This work was supported by National Science Council under Grant NSC81-0404-Em-010 and Telecommunication Laboratories, Directorate General of Telecommunications, Ministry of Transportation and Communication, under Contract TL-NSC-81-5209, Taiwan, Republic of China. J.-F. Yang is with the Department of Electrical Engineering, National Cheng-Kung University, Tainan, Taiwan, R.O.C. C.-L. Lu is with the Computer and Communication Research Laboratory, Industrial Technology Research Institute, Hsinchu, Taiwan, R.O.C. EEE Log Number 9412470.",
year = "1995",
month = aug,
doi = "10.1109/83.403419",
language = "English",
volume = "4",
pages = "1141--1146",
journal = "IEEE Transactions on Image Processing",
issn = "1057-7149",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "8",
}