基于游程和扩展指数哥伦布编码的任意形状感兴趣区域图像编码

摘要

给出一种上下文自适应的游程编码和扩展指数哥伦布编码.利用游程编码算法对图像小波系数及ROI掩模进行上下文自适应建模并输出三元组样本;然后扩展普通的指数哥伦布编码,使其可以编码由游程编码建模输出的三元组样本,在对小波系数编码的同时可以携带感兴趣区域掩模标记信息.由此得到一种可以区别感兴趣区域和背景区域的高效编码算法,并以此算法为基础提出一种感兴趣区域编码的编解码框架,该框架包括5/3小波变换、小波域掩模标记生成、不均匀最佳量化、游程编码和扩展的指数哥伦布编码.该算法的游程建模过程简单,熵编码算法可用闭合公式表达,具有较高的可实现性.实验结果表明,提出的算法支持多个任意形状的感兴趣区域,感兴趣区域相对于背景区域的编码优先级可调,并且可以获得高于基于BbB-shift的SPIHT算法的压缩性能.%A context adaptive tri-element Run length coding algorithm and an Exp-Golomb coding alogorithm were introduced. The Run-length coding was used to model the image wavelet coefficients and the Region of Interest(ROI) mask and to yield tri-element codes. Then, the conventional ExpGolomb coding was expanded to encode tri-element codes from Run-length coding and to carry the ROI mask together. Based on the two algorithms above,a high efficient algorithm to distinguish the ROI and background was obtained and a ROI codec framework was proposed. The framework includes 5/3 wavelet transform, wavelet domain mask generation, non-uniform optimal quantization, context adaptive tri-element Run-length coding and generalized Exp-Golomb coding. The tri-element Run-length coding in this algorithm is brief, and the expanded Exp-Golomb coding can be expressed by a closed formula. Experimental results show that the algorithm supports multiple arbitrary-shaped ROI and the adjustability of the ROI is prior to that of the background region. Furthermore, it achieves higher compressing performance as compared with the BbB-shift based SPIHT compression algorithm.