针对极低码率下图象的压缩编码问题，在小波零树编码方法的基础上提出了一种新的低码率图象压缩算法，该方法对处于水平和垂直两个方向的高频子带系数采用变换的方法进行了系数重排，以产生新的树结构，这样使得位于这两个方向的高频子带内的重要纱数集中于各个相应子带的低频位置，且所生成树的能量集中性较好，故可以有效地提高编码效率，并能提高对重要系数的传输效率，经过实验证明，使用此方法得到的重构图像其主观视觉效果良好，而且与Shapiro提出的嵌入式零树小波（EZW）算法相比，重构图象的峰值信噪比（PSNR）值在梓同码率的情况下有了较大的提高。

In this paper, a new low bit rate image compression algorithm based on wavelet zero tree image coding scheme is put forward. The coefficients in the horizontal and vertical orientation sub images of all scales are reordered by the means of the transform because there are many big energy coefficients. The target of doing so is to produce new tree structure, to add the number of zero tree. And the significant wavelet coefficients in these sub images are concentrated in the low frequency area of the corresponding subbands. So the energy of these sub images is concentrated in the area of the corresponding left hand, and the con centration property of the new trees is good, and it can improve the encoding efficiency effectively. It also can improve the transmission rate of the significant coefficients. The results of the reconstruction images are good. And bit allocation is optimized and the peak signal to noise ratio ( PSNR ) of the reconstructed image is improved compared to embedded zero tree wavelet encoding(EZW) algorithm at the same bit ratio.