Image Compression Using Tree Structured Vector Quantization with Compact Codebook

The science of obtaining a compact representation of a signal while maintaining all the necessary information is referred to as Compression. It can be classified into two types, Lossless and Lossy compression. Lossy compression can be broadly classified into two types, namely Scalar Quantization (SQ) and Vector Quantization (VQ) .VQ since about 1980, become a popular technique for source coding of image and speech data [1]. SQ involves processing the input samples individually using some distortion measure while VQ involves processing the input samples in groups into a set of well-defined vectors using some distortion measure. The direct use of VQ suffers from a serious complexity barrier. The classical technique of TSVQ was introduced by Buzo et al. [2]. This paper discusses the Tree Structured Vector Quantization design for image compression with compact codebook approach.