Quadtree Segmented Double Predictor DPCM Image Compression
Assistant Professor, Dept. of Communications, Navigation and Control Engr., National Taiwan Ocean University, Keelung, Taiwan
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This study is to improve image data compression performance based on variable block-size quadtree image segmentation applied to double predictor differential pulse code modulation (DP–DPCM) image compressive algorithm. The quadtree segmentation method is applied to better allocate image characteristics. A variable block-size double predictor DPCM (VBDP–DPCM) image coding system works on an image been preprocessed into segments of variable size, square blocks, and each block is separately encoded by a DP–DPCM algorithm. Quadtree segmentation method is utilized to divide a given real-world image into variable size image blocks. The detail regions comprise more image features of a given image is segmented into blocks with smaller block size, and the background regions of the image will be assigned larger block size to the image blocks. After quadtree segmentation process, the average dissimilar values between the nearby pixels within an image block are abridged. Therefore, we can decrease the distribution range of the prediction error anddiminish the quantization levels as well as the coding bit rate. We then adopt the double predictor DPCM technique to moderate the effect from the fed-back quantization error and not to augment the system complexity. The compression performance of this proposed method is about 5dB (or greater) coding gain in Signal-to-Noise Ratio (SNR) than that of a conventional DPCM system.