Chung King-Hong, Chan Yuk-Hee
Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hong Kong.
IEEE Trans Image Process. 2008 Feb;17(2):134-44. doi: 10.1109/TIP.2007.914153.
In most digital cameras, Bayer color filter array (CFA) images are captured and demosaicing is generally carried out before compression. Recently, it was found that compression-first schemes outperform the conventional demosaicing-first schemes in terms of output image quality. An efficient prediction-based lossless compression scheme for Bayer CFA images is proposed in this paper. It exploits a context matching technique to rank the neighboring pixels when predicting a pixel, an adaptive color difference estimation scheme to remove the color spectral redundancy when handling red and blue samples, and an adaptive codeword generation technique to adjust the divisor of Rice code for encoding the prediction residues. Simulation results show that the proposed compression scheme can achieve a better compression performance than conventional lossless CFA image coding schemes.
在大多数数码相机中，会捕获拜耳彩色滤光片阵列（CFA）图像，并且通常在压缩之前进行去马赛克处理。最近，人们发现先压缩方案在输出图像质量方面优于传统的先去马赛克方案。本文提出了一种针对拜耳CFA图像的基于预测的高效无损压缩方案。它利用上下文匹配技术在预测像素时对相邻像素进行排序，采用自适应色差估计方案在处理红色和蓝色样本时去除颜色光谱冗余，并使用自适应码字生成技术来调整莱斯码用于编码预测残差的除数。仿真结果表明，所提出的压缩方案能够比传统的无损CFA图像编码方案实现更好的压缩性能。
