Study On Image Compression Based On Wavelet Transform

Image is an important two-dimension signal. Because of the huge data it contains, image must be compressed when it is stored or transported. The wavelet transform (WT) is a rising mathematical tool. The technology of image compression based on wavelet has drawn much attention and has been researched broadly. When a image is transformed by the wavelet, it has favorable localize characteristic in both time-domain and frequence-region. And in the rebuild image the connatural diamonds affection of the discrete cosine transform can be overcame. Furthermore, the WT is identical to Human Visual System(HVS).This paper is mainly about the static image compress algorithm based on wavelet transform, and complete these work: Introduced the theory and technique of traditional image coding and WT coding. Enumerated the prevalent image compressional standards. This paper focuses on the famous WT coding algorithm which named embedded zerotree wavelet (EZW) algorithm and its improved form SPIHT algorithm, based on EZW and SPIHT, an improved algorithm is introduced which includes using the lifting scheme to reduce the complexity of the original WT. To improve the subjective quality, use the Mannos template which accord to HVS to reset the magnitude of the coefficients for each sub-image. To reduce the complexity more, use new threshold scheme in EZW process, default the sign of coefficients in low frequence subimage to positive in SPIHT process, so the deferent code cut down and the coding efficiency improved.The simulation results show that, although the improved algorithm has a lower performance on PSNR compared with classical EZW and SPIHT, its complexity decreases and the way of its coding is more in accord with Human Visual System, so it is more effective.