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改进的分级图像矢量量化
Improved Hierarchical Vector Quantizer of Images
【摘要】 提出了一种基于Peano扫描的分级矢量量化算法,通过有效地利用数据间的相关性,改进了VQ的性能.该算法先通过能比光栅扫描更好地保存二维数据间的相关性的Peano扫描对原始图像进行预处理,再根据信号特性进行分级VQ;还提出了基于Peano扫描的平滑算法,有效地减小了方块效应的影响
【Abstract】 To improve the performance of a compression algorithm based on VQ, a hierarchical VQ based on the characteristics of image data is presented. A HR (high rate) vector quantizer and a LR (low rate) vector for variable rate compression are designed with various vector dimensions and thresholds for segmentation, using quad tree and Bin tree respectively in segmentation. Classified data are encoded using TC/VQ and spatial VQ according to their characteristics. A smoothing algorithm reduces the blocking effect. Compared with standard algorithms, better objective and subjective performances are shown in the algorithms.
【Key words】 image compression; hierarchical vector quantization; Peano scanning; smoothing algorithm;
- 【文献出处】 华中理工大学学报 ,JOURNAL OF HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY , 编辑部邮箱 ,1999年02期
- 【分类号】TP391.4
- 【被引频次】2
- 【下载频次】33