This article introduces a digital watermarking technology based on adaptive quadtree fractal coding.
提出了一种基于自适应四叉树分形编码的数字水印技术。
This paper first introduces the common image compression technology-Huffman coding and fractal coding, and then proposes some improvements.
本文通过介绍常见的图像压缩技术——哈夫曼编码和分形编码，提出了一些改进的方法。
The traditional method of using fractal coding to embed watermarking often took a long time, which also strongly influenced the quality of images.
传统的利用分形编码嵌入数字水印的方法所需编码时间较长，对图像质量的影响大。
For traditional watermarking techniques based on fractal coding, watermarking format is limited to binary sequence 0, 1, thus incapable of gray-scale image embedding.
传统的基于分形编码的水印技术一般嵌入0,1序列，没有实现灰度图像嵌入。
An efficient scheme for video coding is presented which utilizes progressive fractal coding, called wavelet-based fractal approximation (WBFA), and motion compensation (MC).
利用改进的分形编码提出了一种有效的视频编码方法，称作基于小波分形逼近(WBFA)，和运动补偿(MC)。
We firstly overview the properties of fractal coding in image domain, then we derive the corresponding formula of scaling factor and offset of affine transform in DCT domain.
首先，综述了图像域中分形编码的特性，然后导出在离散余弦变换(简称DCT)域中仿射变换的伸缩因子和偏移量的对应公式。
Chapter 3 describes the basic principle of fractal image coding, gives the description and implementation of the baseline fractal coding algorithm, and discusses experimental results.
第3章介绍基本分形编码算法的原理、算法的描述与实现以及实验结果的讨论。
Chapter 3 describes the basic principle of fractal image coding, and gives the description and implementation of the baseline fractal coding algorithm, and discusses experimental results.
第3章介绍分形编码的基本原理、基本分形算法的描述与实现，以及实验结果的讨论。
Fractal coding has been proved useful for image compression, and it is also proved effective for content-based image retrieval.
分形编码在图像压缩方面取得了很好的效果，同时也能够用于基于内容的图像检索。
Fractal singular value neighbor distance is brought forward based on fractal neighbor distance. Fractal coding and local singular value decomposition are used to improve the recognition rate.
在分形近邻距离的基础上，提出了分形奇异值近邻距离，并把分形编码和局部奇异值分解结合起来，提高了识别率。
Fractal singular value neighbor distance is brought forward based on fractal neighbor distance. Fractal coding and local singular value decomposition are used to improve the recognition rate.
在分形近邻距离的基础上，提出了分形奇异值近邻距离，并把分形编码和局部奇异值分解结合起来，提高了识别率。
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