International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 154 - Number 8 |
Year of Publication: 2016 |
Authors: A. Divya, S. Sukumaran |
10.5120/ijca2016912179 |
A. Divya, S. Sukumaran . An Adaptive Vector Quantization Method for Image Compression. International Journal of Computer Applications. 154, 8 ( Nov 2016), 13-16. DOI=10.5120/ijca2016912179
Image compression is to reduce redundancy of the image data in order to store or transmit data in an efficient form. Compression is carried out for the following reasons about reduce, the storage requirement, processing time and transmission duration. The most powerful and quantization technique used for the image compression is vector quantization (VQ). The Existing methods Linde-Buzo-Gray (LBG) and Fast Back Propagation (FBP) algorithm are presented. In existing methods, the compression ratio is decreased. The proposed method adaptive vector quantization is used to analyze for image vector quantization (VQ). The performance of proposed work is analyzed using the factors SNR, MSE, PSNR and CR. The experimental work using MatLab shows that the proposed scheme is efficient and produced expected result.