摘要
为解决传统分形图像编码方案中块匹配时间过长的问题,提出一种结合图像块平均偏差的改进遗传算法,利用改进遗传算法的最优解搜索能力替代分形图像编码中复杂的块匹配过程,结合对比度因子的约束,限定遗传算法的搜索空间,缩短编码时间。实验结果表明,该方法与结合遗传算法的同类改进算法相比,能在缩短编码时间的同时,有效提高解压图像质量。
To overcome the long block matching time of traditional fractal image coding, this paper proposes an improved genetic algorithm which combines with the average variance of image block, uses the improved algorithm＇s optimal solution search capabilities to replace the complex process of block matching in fractal image coding. Combined with the constraints of contrast factor, this method can limit the search space and reduce the coding time. Experimental results show that compared with the other genetic method, the proposed algorithm can speed up the coding process, while improving the image quality.
出处
《计算机工程》
CAS
CSCD
北大核心
2010年第5期205-206,209,共3页
Computer Engineering
基金
国家自然科学基金资助项目(60873058
60743010)
山东省自然科学基金资助重大项目(Z2007G03)
关键词
分形图像编码
遗传算法
平均偏差
fractal image coding
genetic algorithm
average variance
