目的 传统的图像压缩算法大多是基于L₂准则的，但是该方法不能够精确控制每一点的误差，因此提出基于L_∞准则约束的最大误差图像转换压缩算法。该算法能够保证重构的每一点的误差都在给定的范围内。方法 首先利用图像像素点之间的相似性，将图像分解成若干不重叠子块。然后对原始图像的每一子块分别进行完全的转换变换，并存储需要保留的转换系数。最后通过保留的转换系数重构原始图像。结果 实验结果表明，不同分辨率的图像，最适宜的分块大小不相同，随分辨率的增大而增大。结论 与已有的基于L_∞准则约束的最大误差转换压缩算法相比，该算法可以提高图像压缩比和重构质量，并且具有更快的压缩速度。

Objective Traditional image compression algorithms are mostly based on L₂ norm. However, those methods are not able to precisely control the error of each point. In this paper a maximum error image shift compression algorithm based on L_∞ norm is proposed. The algorithm can guarantee that the error at each point of the reconstructed image is limited in a given range.Method First，the algorithm takes the advantage of the image pixel similarity to decompose the image into many non-overlapping sub-blocks. Then each sub-block should be completely shifted, and the retained shift coefficients must be stored. Finally, the original image can be reconstructed by the retained shift coefficients.Result The experimental results show that, the suitable block size of the images of different resolutions is not the same, which increases by the increase of image resolution. Conclusion Compared with the existing algorithm based on L_∞ norm maximum error shift compression, the compression ratio, reconstructed image quality and compression speed can be improved by the proposed algorithm.