New Method of Image Compression Using Multiwavelets and Set Partitioning Algorithm

Abstract

Advances in wavelet transforms and quantization methods have produced algorithms capable of surpassing the existing image compression standards like the joint photographic experts group (JPEG) algorithm. The existing compression methods for JPEG standards are using DCT with arithmetic coding and DWT with Huffman coding. The DCT uses a single kernel where as wavelet offers more number of filters depends on the applications. The wavelet based set partitioning in hierarchical trees (SPIHT) algorithm gives better compression. For best performance in image compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry, but they cannot simultaneously possess all of these properties. The relatively new field of multiwavelets offer more design options and can combine all desirable transform features. But there are some limitations in using the SPIHT algorithm for multiwavelet coefficients. This paper presents a new method for encoding the multiwavelet decomposed images by defining coefficients suitable for SPIHT algorithm which gives better compression performance over the existing methods in many cases.