为了提高提升框架下整数小波变换(IWT)对图像的有损编码效率，需要在提升步骤中引入缩放因子。但是，缩放因子通常为无理数，需增加3个额外的提升步骤用以保证变换结果的整数特性，这不仅增加了计算复杂度而且加大了截断误差对图像压缩的影响。提出一种结合最优缩放框架与四叉树分割的图像编码算法，在对图像进行无缩放因子的整数小波分解后，各子带仅乘一次缩放因子，降低了变换的计算复杂度。在编码过程中，利用新的四叉树分割框架提高重要系数的搜索效率。实验结果表明，新算法不仅获得了较好的图像有损压缩效率，而且较一般IWT具有更低的计算复杂度，对今后遥感与医学图像压缩具有一定价值。

For improving the lossly image coding efficiency of integer wavelet transform (IWT) based on lifting scheme, the scaling factor is used in the lifting steps. However, the scaling factor is often an irrational number, which requires three additional lifting steps to assure the integer character of transform results. They not only increase computational complexity of integer wavelet transform, but also raise the effect of rounding error on image compression. This paper presents a new image coding algorithm using optimal scaling scheme and quadtree partitioning. The new algorithm decomposes the image using integer wavelet without scaling factor and then only performs a multiplication on every subband with the new scaling factor, which reduces the computational complexity of the integer wavelet transform. During the image encoding, a new quadtree partitioning scheme is used to improve the searching efficiency of the significant coefficients. The experimental results show that the new coding algorithm has not only the well lossly compression efficiency, but also the lower computational complexity than the common IWT. This new method is valuable for future remote sensing and medical image compression.