在频域中利用同态滤波增强图像对比度

Image contrast enhancement by homomorphic filtering in frequency field

在介绍基于照明反射模型的同态滤波模型原理、实现过程和特点的基础上,在频域内通过对高斯高通滤波器、巴特沃斯高通滤波器、指数高通滤波器的改进后得出三种同态滤波器,并对三种同态滤波器通过实验结果给出适用的滤波模型和表达式参数。由对同一幅照明不良会使图像亮度不足和细节模糊,而且图像信噪比很低,图像对比度明显变差的图像处理结果表明,巴特沃斯同态滤波函数优于其它两种同态滤波函数,对光照不足的图像进行灰度动态范围压缩和对比度增强效果显著。

In digital image processing, the homomorphic fikering approach is derived from an illumination-reflectance model of the image. Homomorphic filtering can perform simultaneous dynamic range compression and contrast enhancement. Crucial for the success of the homomorphic approach is the selection of an appropriate frequency-domain fiher function in order to modify the illumination and reflectance components of an image differently. The author used Butterworth equations, Gaussian equations and Exponent equation to enhance image contrast by modifying Butterworth type highpass equations, Gaussian type highpass equations and Exponent type highpass equation. The Butterworth homomorphic filtering equations far superior to other frequency-domain filter functions, including Gaussian equations, making the Butterworth homomorphic suitable for use with the homomorphic filtering approach.