A novel approach for near-lossless compression of Color Filtering Array (CFA) data in wireless endoscopy capsule is proposed in this paper. The compression method is based on pre-processing and vector quantization. First, the CFA raw data are low pass filtered and rearranged during pre-processing. Then, pairs of pixels are vector quantized into macros of 9 bits by applying block par-tition and index mapping in succession. These macros are entropy compressed by Joint Photographic Experts Group-Lossless Standard (JPEG-LS) finally. The complex step of codeword searching in Vector Quantization (VQ) is avoided by a predefined partition rule, which is suitable for hardware imple-mentation. By control of the pre-processor and VQ scheme, either high quality compression under un- filtered case or high ratio compression under filtered case can be realized, with the average Peak Sig-nal-to-Noise Ratio (PSNR) more than 43dB and 37dB respectively. Compared with the state-of-the-art method and the previously proposed method, our compression approach outperforms in compression performance as well as in flexibility.
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机译:A novel approach for near-lossless compression of Color Filtering Array(CFA)data in wireless endoscopy capsule is proposed in this paper.The compression method is based on pre-processing and vector quantization.First,the CFA raw data are low pass filtered and rearranged during pre-processing.Then,pairs of pixels are vector quantized into macros of 9 bits by applying block par-tition and index mapping in succession.These macros are entropy compressed by Joint Photographic Experts Group-Lossless Standard(JPEG-LS)finally.The complex step of codeword searching in Vector Quantization(VQ)is avoided by a predefined partition rule,which is suitable for hardware imple- mentation.By control of the pre-processor and VQ scheme,either high quality compression under an- filtered case or high ratio compression under filtered case can be realized,with the average Peak Sig- nal-to-Noise Ratio(PSNR)more than 43dB and 37dB respectively.Compared with the state-of-the-art method and the previously proposed method,our compression approach outperforms in compression performance as well as in flexibility.
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