基于子带分解的MSR雾天图像增强算法

提出了一种基于子带分解的MSR的图像增强算法(Subband-Decomposed Multiscale Retinex,简称SDMSR).先利用改进后的MSR算法对雾天图像进行处理,之后由子带分解的方法对雾天图像的不同子带分解输出进行增益,最后采用图像融合技术得到清晰的增强图像.并借助均值、标准差、熵、均方误差(MSE)和峰值信噪比(PSNR)对文中算法的仿真结果进行了定量评价,仿真与评价结果表明,该算法能够提高雾天图像的对比度,保留了原图像中有用的信息,图像的失真程度小,图像的清晰度也得到了提高.

Multi-scale Retinex Algorithm for the Foggy Image Enhancement Based on Sub-band Decomposition

A kind of Multi-Scale Retinex (MSR) algorithm based on sub-band decomposition for image enhancement was proposed.First,the improved MSR algorithm was used to deal with the foggy image.Then,the gain of the different foggy image was obtained by the sub-band decomposition method.After that,the clear and enhanced image was obtained by the image fusion technology.At the same time,the simulation results of the algorithm was analyzed by using the mean value,standard deviation,entropy and mean square error (MSE) and peak signal-to-noise ratio (PSNR).The simulation and evaluation results show that the contrast of image is increased,the useful information of the original image is retained,the degree of distortion is small,and the clarity of the image can be improved.