基于同态滤波及多尺度Retinex的低照度图像增强算法

针对在彩色图像采集过程中,光源偏暗或曝光不足等因素,常导致图像亮度和对比度偏低问题,提出了一种改进的低照度图像增强算法。首先用改进的同态滤波增强低照度图像的RGB各分量;然后将RGB图像转换到HSV彩色空间,对饱和度分量进行自适应非线性拉伸;同时用改进的多尺度Retinex算法对亮度进行增强处理,对照射分量用伽马变换进行校正,对反射分量用Sigmoid函数进行处理,最后将图像再转换至RGB空间。用MATLAB对图像进行仿真处理。实验表明该算法提高了低照度图像的信息熵、峰值信噪比和对比度,提升了低照度图像的视觉效果。

Low - intensity Image Enhancement Algorithm Based on Homomorphic Filtering and Multi- scale Retinex

Aiming at the problems of low brightness and low contrast often caused by the dark or underexposed light source in the process of color image acquisition, an improved low illumination image enhancement algorithm is proposed. First, the improved homomorphic filter is used to enhance the RGB components of the low-illumination image. Then the RGB image is converted into the HSV color space to adaptively stretch the saturation component S nonlinearly. At the same time, an improved multi-scale Retinex The algorithm enhances the brightness V, corrects the illumination component L with gamma transform, processes the reflection component R with Sigmoid function, and finally converts the image to RGB space again. Experimental results show that the proposed algorithm improves the entropy, peak signal-to-noise ratio and contrast of low-illumination images and enhances the visual effects of low-illumination images.