【作者】 陈丽华；

【导师】 沈建国；

【作者基本信息】 华东师范大学 ， 通信与信息系统， 2006， 硕士

【摘要】 现今社会，互联网技术正在迅猛的发展，以图像为主的多媒体技术大大丰富了我们的生活。但是如果没有一个高效的压缩方法，图像通信将不可能实现。图像压缩编码的目的就是要以尽量少的比特数表征图像，同时保持复原图像的质量，使它符合特定应用场合的要求。图像压缩也是多媒体技术的关键和瓶颈之一。 到目前为止，图像压缩的研究己经产生了一些成熟的技术，如DCT变换，霍夫曼编码等。并且以这些编码为基础己形成了一系列的国际标准，如BIG，JPEG，JPEG—2000，H.261，H.263，MPEG—1，MPEG—2，MPEG—4，MPEG—7等。 图像压缩编码技术目前又提出了许多新的编码方法，如子带编码、小波变换编码、利用分形几何的图像编码等等，尤其是分形编码，突破了原有编码的界限，对于某些图像而言，有着其它传统压缩算法无可比拟的压缩比，引起了人们的极大关注。 分形编码是一个非常前沿性的新事物，虽然在理论上它具有很大的优越性，但是在实践上人们对它的研究才处于萌芽阶段。传统分形压缩算法是在对子块(Range)和父块(Domain)进行了大小不同的分割后，在整个图像范围内寻找子块在压缩、仿射变换下的最佳匹配父块。由于每个父块一般都对应着8种仿射变换，所以搜索压缩映射块的过程消耗了大量的时间，压缩速度的缺陷足以抵消其优越性。因此，本文以基于分形基本理论的图像编码研究为目的，在系统地介绍了分形压缩的基本理论后，针对传统方法耗时长的缺点，提出了一种非压缩的均方差编码算法，即对子块和父块进行大小相同的分割，这样不但减少了压缩的时间，同时也达到了压缩的目的。之后，通过计算父块间均方差值的大小，精简父块数量，并放弃了传统的8种仿射变换，大大节约了整个算法的运行时间。 分形与小波技术相结合是近几年的一个热点，本文最后提出了与小波编码相结合的初步设想。更多还原

【Abstract】 As the technology of Network quickly develops, the multimedia technology based on image enriches our lives. However if there is no highly effective compression approach, image communication can not be achieved. The purpose of image compression coding is to represent images with few bits, maintain the quality of recovering images according to the requirements of certain application situations. Image compression is the key and bottleneck of multimedia technology.Up to now, some mature technologies have been developed in the area of image compression, such as DCT (Discrete Cosine Transform)and Huffman Code. Moreover, a series of international standards based on these coding algorithms, for example, BIG, JPEG, JPEG-2000, H. 261, H .263, MPEG -1, MPEG-2, MPEG-4 and MPEG-7.Recently, many new coding methods have been proposed, such as Subband Coding, Wavelet Transform Coding and Fractal Image Coding. Fractal Image Coding gets our great attention because it breaks the limit of previous coding and obtains the maximum compression ratio comparing with other algorithms.Fractal Image Coding is a novel technology. Though in theory it has great advantages, in practice the research on it is just on the beginning stage. Traditional Fractal Image Coding first divides the image into ranges and domains at different size, and then searches the best matching domain of a range in the whole image after compressing and affine transforming the domains. Since each domain commonly corresponds to eight affine transforms, the process of searching compression mapping block cost vast time. The advantages of traditional fractal coding are counteracted by the low speed of compression. Therefore, after researching on basic theories of fractal compression, we propose a non-compression algorithm based on root mean square error (RMSE). The new method divides the image into ranges and domains at the same size. This procedure not only reduces the compression time, but also achieves the purpose of compression. After division, the new approach reduces the number of domains by computing RMSE between every two domains. In addition,更多还原