【摘要】 以模糊C-均值聚类(FCM)理论为基础,提出一种新的快速分形图像编码算法.该算法首先将原始图像划分成子块和父块,并对父块实施8种基本变换以生成父块组;然后对所有子块和父块组进行FCM聚类;最后选取隶属度最大的父块变换再进行分形编码.仿真实验表明,本文所提出的快速分形图像编码算法是一种高效的图像压缩方法,不仅其压缩效果明显优于K-均值聚类分形图像压缩方案,而且具有较短的编解码时间.更多还原

【Abstract】 Fractal image coding can provide a high reconstructed image quality with a high compression ratio, but it suffers from long encoding time, for fractal image coding must spend long time on finding out the best-matched block from a large domain pool to represent each of range blocks. In this paper, a fast fractal image compression based on fuzzy C-means clustering is proposed, which can search out the best-matched block to an input range block with a reduced search. Firstly, the origin image is split into range blocks and domain blocks, and 8 elementary transform are performed on domain blocks to obtain the domain blocks group. Secondly, all range blocks and domain blocks group are clustered by fuzzy C-means clustering (FCM). Finally, domain block transform with the biggest fuzzy membership are encoded. Experimental results show that the proposed image coding is a fast and efficient image compression scheme; it can considerably shorten the encoding time, while achieving the same or better decoded image quality.更多还原