Department of Mathematics, Harbin Institute of Technology, Harbin, China.
IEEE Trans Image Process. 2012 Mar;21(3):958-67. doi: 10.1109/TIP.2011.2169272. Epub 2011 Sep 23.
This paper introduces a class of adaptive Perona-Malik (PM) diffusion, which combines the PM equation with the heat equation. The PM equation provides a potential algorithm for image segmentation, noise removal, edge detection, and image enhancement. However, the defect of traditional PM model is tending to cause the staircase effect and create new features in the processed image. Utilizing the edge indicator as a variable exponent, we can adaptively control the diffusion mode, which alternates between PM diffusion and Gaussian smoothing in accordance with the image feature. Computer experiments indicate that the present algorithm is very efficient for edge detection and noise removal.
本文提出了一类自适应 Perona-Malik (PM) 扩散模型，它将 PM 方程与热方程相结合。PM 方程为图像分割、噪声去除、边缘检测和图像增强提供了一种潜在的算法。然而，传统 PM 模型的缺陷是容易导致阶梯效应，并在处理后的图像中产生新的特征。利用边缘指示符作为变量指数，可以自适应地控制扩散模式，根据图像特征在 PM 扩散和高斯平滑之间交替。计算机实验表明，该算法在边缘检测和噪声去除方面非常有效。
