Julia集在分形压缩编码中的应用  

Fractal Image Compression Coding Using Julia Collection

作　　者：赵德平[1] 杨迁[2] 许占利[3] 

机构地区：[1]沈阳建筑大学图书馆,辽宁沈阳110168 [2]沈阳建筑大学信息与控制工程学院,辽宁沈阳110168 [3]沈阳建筑大学组织部,辽宁沈阳110168

出　　处：《沈阳建筑大学学报（自然科学版）》2005年第6期736-739,共4页Journal of Shenyang Jianzhu University：Natural Science

基　　金：辽宁省自然科学基金(1022038-1-04)

摘　　要：目的构建一固定的压缩字典.改变传统的一副图像对应一个压缩字典的分形图像压缩方法.提出了分形图在分形图像压缩算法中的应用.方法采用f(z)=z2+C,对不同的C,有不同的曲线.用灰度值量化规则进行量化,得到一幅图像.这样可以得到丰富的压缩字典.将量化后的4×4 Julia量化曲线与原图的4×4图像块进行比较,选取豪斯多夫度量最小的Julia量化曲线.解码过程读取压缩字典,重建原图像.结果通过与传统的分形图像压缩算法比较,该算法编码过程生成丰富的压缩字典,所以解码图像质量高.并且比传统分形图像压缩算法的压缩比高,解码速度快.结论用固定分形图像压缩编码字典替代变化的分形图像压缩编码字典,使得压缩字典和要处理的图像不再一一对应.将父类进行简单的分类,减少了搜索时间.实验证明本算法实现简单、可行.图像压缩理想,效果很好.A steady dictionary is constructed to change the fact that an image has only one compression dictionary. How to use fractal image in fractal image compression is presented, f（z） = z^2 ＋ C with a different C and a different curve is used to measure the curve and get an image which can obtain abundant compression dictionary. Comparing the 4 ×4 measured curve with the 4× 4 image block of the former image, the measured curve of the minimum Hausdorff measurement is chosen to read compression dictionary and recon- struct the former image in decoding process. Compared with traditional algorithm, this decoding image of abundant compression dictionary is of high quality. It also has a high compression ratio and a high decoding speed. Using this algorithm for compression is good and can obtain a nice result.

关 键 词：JULIA集 分形 图像压缩 压缩字典 Julia量化曲线 编码 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]