A new decoded image quality prediction algorithm for fractal image coding was proposed.
对于分形图像编码算法，提出一种解码图像质量的预测方法。
This paper proposed an improved scheme for fractal image coding by introducing a control parameter that can affect the decoded image quality as well as encoding speed.
通过引入一个可以影响解码图像质量和编码时间的控制参数，该文提出了分形图像编码的一种改进方案。
The paper analyses the weakness of traditional speed-up techniques for image fractal compression firstly, and proposes a novel idea by using entropy to improve image fractal compress performance.
本文首先分析图像分形压缩技术中传统加速方法的性能缺陷，随后提出使用图像块的熵值来改进分形压缩性能的思想。
This paper proposes a correlation-coefficients-based scheme for fast fractal image encoding, which does not need to change the existing fractal decoding procedure.
该文提出了快速分形图像编码的一种基于相关系数的编码方案，不需要改变现有的分形解码过程。
In this paper, a kind of generalized multiscale fractal parameter is proposed and constructed for the description of image textures, which is based on fractional Brownian random field model.
本文从分数布朗随机场模型的描述出发，提出并构造了一种广义多尺度分形参数，用于描述图像的纹理信息。
Fractal image compression has received much attention for its desirable properties like resolution independence, fast decoding and high compression ratio.
基于分形的图像编码方法具有高压缩比、分辨率无关性、快速解码等优越性质。
The general fractal dimension algorithms of image have the disadvantage of the precision and the speed especially when applied to the high dimension images for the moment.
分析了当前计算图像分形维数的算法普遍存在对高维数图像计算误差较大且计算量大的缺点。
It is shown that the improved DBC approach can convert pavement image to one whose fractal dimension permits simple thresholding for segmentation of pavement cracks.
结果显示差分计盒方法可以将路面图像转换成另一种图像，该图像的分形维数可以把简单的阈值应用到路面裂缝的分割。
At first, the fractal dimension is extracted from the original image and special gray image for the rough classification, and then the multi-fractal dimension is used for further classification.
首先通过计算原始图像和特征灰度图像的分形维数实现第一次的粗分类提取，然后采用多重分形奇异谱方法进一步完成了细分。
The nowadays fractal image compression schemes suffers from long encoding time, because of considerable comparisons with domain blocks for each range block to find its best-match domain blocks.
目前分形图像压缩的最主要问题是其编码时间太长，这主要是因为在分形编码时，对每一个待编码值域块都需要比较数量巨大的定义域块才能找到它的最优匹配块。
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。
Combining image signal processing technique, particle size information can be obtained by computing fractal dimension values, and then a new method for particle sizing will be developed in future.
结合图象信号处理技术，可从计算的分形维值中获取粒度信息，进而可得到一种超细微粒粒度测试的方法。
However, the long coding time of this method becomes the main problem for the fractal image compression to be efficient and utilizable.
分形图像编码速度慢的最主要原因是搜索最佳匹配的定义域块耗时太多。
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。
In this paper, fractal image coding and fractal interpolation for image compression are studied at first.
本文首先研究了分形图象压缩编码和分形插值图象压缩方法。
Based on digital image processing and fractal, multifractal spectrum was applied to wood inner defects recognition, the range of multifractal spectrum was set for wood image detection.
基于数字图像处理技术和分形理论，应用多重分形频谱理论对木材内部缺陷进行识别，并设定了适用于木材图像检测的分形频谱值范围；
An improved fractal image denoising algorithm for removing additive white Gaussian noise (AWGN) was presented by adopting quadratic gray-level function.
提出了一种针对加性白高斯噪声(AWGN)的改进分形图像去噪方法。
This paper proposes a method for edge detection of image based on fractal theory and mathematical morphology.
提出一种基于分形理论和数学形态学的边缘检测方法。
This paper proposes a method of rule composition based on fractal image primitives for fractal composition.
针对分形构图，提出一种基于分形图元的规则构图方法。
It USES wavelet and fractal to compress image and compare its compression result. Then sum-up what is fit for wavelet and fractal compression.
本课题就是针对上述问题，通过小波变换和分形这两种方法来进行图像压缩，对比起压缩效果，总结出分别适合于小波和分形压缩的图像。
The popular method for fractal dimension estimation is box-counting method, but as to gray level images, the results are so coarse that they could hardly be used as the feature for image analysis.
目前计算分数维广泛采用的方法是盒维数法。但对于灰度图像而言，盒维数计算的结果太粗略以致于很难将它作为进行图像分析的特征。
Based on the idea, a new concrete algorithm for realizing fractal image coding is designed in the paper.
根据此思想给出了一个新的具体实现分形编码的算法。
This paper presents a new method for fast fractal image coding.
提出了一种新的快速分形图象编码方法。
In this paper, we proposed a fractal characters based method for nature environment image segmentation.
提出了一种基于分形特征分割自然景物图象的方法。
In this paper, we proposed a fractal characters based method for nature environment image segmentation.
提出了一种基于分形特征分割自然景物图象的方法。
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