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机构地区:[1]东北大学信息科学与工程学院,辽宁沈阳110004 [2]东北大学计算中心,辽宁沈阳110004 [3]沈阳建筑工程学院计算机系,辽宁沈阳110015
出 处:《东北大学学报(自然科学版)》2002年第9期825-828,共4页Journal of Northeastern University(Natural Science)
基 金:国家自然科学基金资助项目 (69973 0 3 3 )
摘 要:根据统计规律建立一个小型固定字典 ,用以加速分形图像的压缩编码 ;然后 ,用Julia图像的生成的图像块作为分形图像压缩编码字典的补充 ;还建立一个编码和解码都相同的平均值字典·因此 ,使用的压缩方法改变了由常规设计的传统分形图像压缩编码使用编码和解码不相同字典进行编码和解码的缺点·实验结果表明 ,所使用的方法能很好地对图像进行分形压缩编码和解码 ,和常规分形编码方法相比还具有较高的PSNR·A small fixed compression dictionary was built according to statistical law to speed up fractal image compression coding. Many 8×8 image blocks were then created by the escaping method to produce Julia images by using the image blocks in fractal image compression coding. Finally, a mean image compression dictionary was created that is the same as the image decompression dictionary. Therefore, the compression algorithm can correct the defect of using an image compression dictionary that is not same as the image decompression dictionary in the conventional fractal image compression coding. The experimental results show that the algorithm can realize fractal image coding and decoding very well and also it has better PSNR than the conventional fractal image compression coding.
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