摘要
由曼德勃罗特(Benoit B.Mandelbrot)的分形理论可知,建立在分形布朗运动模型之上的医用图像总可以计算得一分形维数。本文对建立于分形布朗运动模型之上的分形维数的估算进行了讨论。通过将整个医用图像中每个像素的分形值,转化为相应象素的灰度值,得到了边缘增强和检测图。结果显示:基于分形的医用图像转化算法较之传统的图像边缘增强算法有利于减少噪声。
According to Mandelbrot's fractal theory, it was found that the fractal dimension could be obtained in medical images by the concept of fractional Brownian motion. An estimation dimension based upon the concept of fractional Brownian motion is discussed. An edge enhancement and detection image is obtained by transforming the fractal dimension value of each pixel over the whole image to the gray value of it. Results suggest that that fractal based image transformation algorithm can decrease noise better than traditional algorithm in the way that gradient operators do.
出处
《湖北汽车工业学院学报》
2002年第1期36-39,共4页
Journal of Hubei University Of Automotive Technology
基金
国家973项目"C-p医用材料骨诱导性及其机理研究"一部分
关键词
分形布朗运动
边缘增强与检测
噪声
分形维值
fractional Brownian motion
edge enhancement and detection application
noise
fractal dimension
