基于复合分类的快速分形图像压缩编码
Fractal Image Compression Coding Based on Classification and Clustering
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摘要: 针对分形编码方法耗时过长的不足,提出一种分类加聚类的快速分形图像编码方法.通过提取图像块的分形维数对图像块分类,在同类内基于分形维数聚类,使匹配搜索在同类的聚类域内进行,并对不同类块采用不同算法.实验表明,该方法与经典分形方法(PIFS)比较,在信噪和解码图像质量可接受的条件下,大大提高了编码速度,且压缩比有显著提高.Abstract: To reduce the computation time of fractal image coding, an approach based on classification and clustering is proposed. The image blocks are classified into different categories according to the fractal dimensions of image blocks, and the same category is then further divided into several clusters. Matching is done within the cluster, and the blocks in different categories are coded in different ways. Experiment shows that compared with the conventional fractal coding method (PIFS), the coding speed and compression ratio is increased significantly while the signal to noise ratio of it and the decoding image quality is acceptable.
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