首先分析无失真图象编码技术,提出一种基于块方向预测和Context的自适应无失真编码方法,该方法主要使用块方向预测和基于Context的误差模型去除图象在空间上的相关性.在此方法中,一幅图象首先被分割成图象块,对图象的每一块自适应地选择一个使预测误差绝对值之和最小的块方向预测器；然后通过Context选择和误差反馈进一步降低信息熵；最后,采用快速而有效的Rice编码器对误差图象编码.实验结果显示，该方法的压缩效果明显优于JPEG(joint of picture expert group)无失真模式和FELICS(fast and efficient lossless image compression),略好于CB9和LOCO-I,甚至UCM(universal context modeling).
In this paper, lossless image coding techniques are discussed first, then a lossless image coding method based on block direction prediction and context is presented. It removed the redundancy of the image in spatial domain by block direction prediction and context-based error modeling. In the proposed method, an image is first partitioned into blocks. Then, a direction predictor that results in minimum prediction error is adaptively selected for each block. After that, context selection and error feedback are applied to further reduce the entropy. A fast and efficient Rice coder is applied finally for the residual image coding. The experimental results show that the proposed method significantly outperforms over JPEG (joint of picture expert group) lossless mode and FELICS (fast and efficient lossless image compression), and it obtains comparison ratio superior to CB9, LOCO-I, even UCM.