题目/Title：Pre-Processing and Vector Quantization Based Approach for CFA Data Compression in Wireless Endoscopy Capsule

作者/Author：
                        XiaoWen Li,Xinkai Chen,Xiang Xie,Guolin Li,Li Zhang,Zhihua Wang

会议/Conference：ISBI 2007

地点/Location：Arlington, VA

年份/Issue Date：2007.12-15 April

页码/pages：pp. 1172 - 1175

摘要/Abstract：
In wireless endoscopy capsule, an efficient, low-complexity compression approach for Bayer CFA data is critical for the low power design of the entire system. In this paper, a compression approach based on pre-processing and vector quantization is proposed. The CFA raw data are first low pass filtered during pre-processing. Then, pairs of pixels are vector quantized into macros of 9 bits by applying block partition and code mapping in succession. After rearranging, these macros are entropy compressed by JPEG-LS. By control of the pre-processor, both near-lossless and lossy compression can be realized. The effectiveness of our block partition scheme has been demonstrated by statistical experiments. Simulation results show that the proposed approach has a good performance in compression rate as well as reconstructed quality