Embedded Image Compression Using Differential Coding and Optimization Method

Embedded zerotree (EZW) and SPIHT coding, introduced by J.M.Shapiro and Amir Said, are very effective and being used in many fields widely. Embedded zero-tree wavelet encoding is currently the most advanced image coding methods, In this paper, brief explanation of the principles of SPIHT was first provided, and then, some improvement of SPIHT algorithm according to experiments was introduced. For redundancy among the coefficients in the wavelet-region, we propose differential method to reduce it during coding. Meanwhile, In the uniform quantization of wavelet coefficients, the sub-band depending on the context of modeling the probability of the statistical characteristics based on characteristic of the coefficients´ distribution in sub-band, we adjust sorting pass and optimize differential process, in order to reduce the redundancy coding in each sub-band. The image coding result, calculated by certain threshold, showing that through differential optimization, the rate of compression get higher, and quality of reconstructed image have been get raised greatly, when bpp=0.5, PSNR of reconstructed image exceeds that of SPIHT by 0.07~0.12db.