提出了一个多个任意形状感兴趣区域编码框架.通过引入灰度掩膜图像来表示不同感兴趣区域的优先级,在总的目标码率和各个优先级感兴趣区域重建质量的约束条件下,按照优先级从高到低的顺序对不同的感兴趣区域采用整数到整数形状自适应离散小波进行变换,对变换后的系数采用修改的SPIHT算法产生单独的压缩码流.实验结果表明,本编码框架有如下优点：（1）根据感兴趣区域的优先级顺序来保证感兴趣区域的目标重建质量;（2）适合于任意形状感兴趣区域的有损和无损压缩;（3）感兴趣区域重建质量估计方法简单有效.

In this paper,we propose a new multiple arbitrary shape regions-of-interest(ROIs) coding framework.Gray mask is incorporated to manifest the priorities of the multiple ROIs.Multiple ROIs are transformed sequentially by the ISA-DWT according to their priorities with different constraints of the target bitrate and the reconstructed regional fidelity of different priorities.Then the set partitioning in hierarchical trees(SPIHT) algorithm is modified to generate the separate compression bit streams.Experimental results show that the proposed coding framework has the following novelties:(1) it ensures the quality of the reconstructed ROIs according to their priorities;(2) it is fit for arbitrary shape ROI loss and lossless coding;(3) it achieves low complexity by reaching the target ROI PSNR.