Wavelet Analysis and High Quality JPEG2000 Compression Using Daubechies Wavelet

Wavelet analysis and its application has found much attention in recent times. It is vastly applied in many applications such as involving transient signal analysis, image processing, signal processing and data compression. It has gained popularity because of its multiresolution, subband coding and feature extraction features. The paper describes efficient application of wavelet analysis for image compression, exploring Daubechies wavelet as the basis function. Wavelets have scaling properties. They are localized in time and frequency. Wavelets separate the image into different scales on the basis of frequency content. The resulting compressed image can then be easily stored or transmitted saving crucial communication bandwidth. Wavelet analysis because of its high quality compression is one of the feature blocks in the new JPEG2000 image compression standard. The paper proposes Daubechies wavelet analysis, quantization and Huffman encoding scheme which results in high compression and good quality reconstruction.