基于各向异性扩散的弱小目标增强算法(英文)  

Dim Target Enhancement Algorithm for Low-contrast Image based on Anisotropic Diffusion

作　　者：王艳华[1] 刘伟宁[1] 

机构地区：[1]中国科学院长春光学精密机械与物理研究所

出　　处：《光电工程》2008年第6期15-19,共5页Opto-Electronic Engineering

摘　　要：针对弱小目标对比度较低、边缘模糊、难以准确探测的问题,本文提出一种基于PDE的改进的各向异性扩散滤波算法增强弱小目标。该方法根据各向异性扩散原理,通过改进传统的P-M方程建立新的滤波模型,采用自适应滤波的方法在非目标区进行背景平滑,在局部变化的区域进行锐化处理增强弱小目标,从而达到背景平滑的同时增强边缘的效果。同时可以通过调节参数k和w选择平滑和锐化的程度,以适应不同的环境变化。实验结果表明,该方法能够有效的增强低对比度图像中的弱小目标。In a sensed image of long distance, the gray levels of target and background are hardly distinguishable, which results in a tow-contrast image. Dim-target detection is always a difficult problem. The aim of this paper is to propose an anisotropic diffusion filtering algorithm based on partial differential equation to enhance the dim targets. The algorithm establishes a new filter model by improving the traditional P-M model based on the anisotropic diffusion theory. The proposed method adaptively performs the smoothing process in the faultless areas to make the background uniform, and performs the sharpening process in the variational areas to enhance dim targets. Simultaneously, we can ~elect the smoothing and sharpening degree by adjusting the parameter K and w to satisfy different environments. Experimental results show the efficiency of the proposed diffusion scheme in dim-target enhancement with low-contrast

关 键 词：PDE 各向异性扩散 低对比度图像 图像增强 自适应滤波器 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]