An Analysis of Vector Quantization Based Image Compression Approaches
Vector Quantization, Image Compression, Compression Ratio, Lossy Compression, Computation Time.
Digital image processing helps in manipulation of the digital images by using computers. The term image compression refers to the process of reducing the amount of data necessary to represent a given quantity of information. Compression methods are rapidly developed to compress large data files such as images. There are two types of compression techniques are lossy and lossless. Vector Quantization is an essential and fundamental technique for lossy image compression. An efficient image compression technique is essential to achieve better compression for storing and transmitting huge multimedia content. The most popular technique used for the image compression is vector quantization (VQ). In this paper, various VQ based image compression techniques are analyzed and attempt to find out best approach among them. The techniques of VQ based image compression, improvement in metrics such as peak signal noise ratio, mean square error, computation time, fitness value, distortion ratio are briefly discussed.
A.Divya, Dr. S.Sukumaran. "An Analysis of Vector Quantization Based Image Compression Approaches".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.5, Issue 2, pp.1231-1237, URL :https://rjwave.org/ijedr/papers/IJEDR1702199.pdf
Volume 5 Issue 2
Pages. 1231-1237
