This paper presents a lossless color transformation and compression algorithm for Bayer color filter array (CFA) images. In conventional CFA compression algorithms, the compression block is placed after the demosaicking stage. However, in the proposed method, the compression block is performed first. The study used a low complexity four-channel color space aiming to reduce the correlation among the Bayer CFA color components. In the presented method, the color components showed better de-correlation compared to the raw CFA color components. After the color transformation, components are independently encoded using modified differential pulse-code modulation (DPCM) in a raster order fashion. The compression algorithm includes an adaptive Golomb-Rice and unary coding in order to generate the final bit stream. Several verification was performed on both the simulated CFA and real CFA datasets. The results show that the proposed algorithm requires less bits per pixel than the conventional lossless CFA compression technique. In addition, it outperforms the recent works on lossless CFA compression algorithms by a considerable margin.

本文提出了一种用于拜耳彩色滤光片阵列（CFA）图像的无损色彩变换和压缩算法。在常规的CFA压缩算法中，压缩块放置在去马赛克阶段之后。然而，在所提出的方法中，首先执行压缩块。该研究使用了一种低复杂度的四通道色彩空间，旨在减少Bayer CFA色彩成分之间的相关性。在提出的方法中，与原始CFA颜色成分相比，颜色成分表现出更好的去相关性。颜色转换后，使用改进的差分脉冲编码调制（DPCM）以光栅顺序的方式对组件进行独立编码。压缩算法包括自适应Golomb-Rice和一元编码，以生成最终的比特流。对模拟CFA和真实CFA数据集都进行了几次验证。结果表明，与传统的无损CFA压缩技术相比，该算法每像素所需的位数更少。此外，它在无损CFA压缩算法方面的最新表现要好得多。