提出了一种具有渐进多分辨率特性的小波图像压缩算法。对图像作提升小波分解后，首先利用人眼视觉特性，对小波系数作无视觉失真的量化，然后按各子带对视觉效果不同的贡献，在给定的编码比特约束条件下．将比特资源按照率失真曲线最优地分配给各子带，最后以给定的比特量对各子带分别进行分层量化和算术编码，从而达到最小的失真要求。最优分配方法将小波系数建模为广义高斯分布，给出了最优分配给各子带比特数的理论公式，它不需遍历不同的量化阶段，且在率失真意义上最优。实验结果表明，与经典的算法相比．在PSNR相仿的情况下，低码率时有更好的视觉效果，有更优越的综合性能。

This paper presents a new wavelet based image coder with the property of progressive multi-resolution. After the image is decomposed with lift wavelet, the wavelet coefficients are quantized visually lossless by utilizing the properties of HVS. Then, in the constraint of the bits budget, the bits are allocated optimally to each subband according to the rate-distortion curve and their contribution to the visual effect. At last each subband is independently encoded with the procedures of layered quantization and arithmetic coding. Without the iteration of all the quantization steps, the bit allocation algorithm deduces the theoretic formula of allocation by modeling the wavelet coefficients as generalized Gaussian distribution. The allocation result is optimal in the sense of rate-distortion. The experiments show that, compared with the classical coders, the coder has the near PSNR values and the better visual effect in low bit rate such that it displays the superior performance.