均场退火算法在单幅灰度图像高光检测与恢复中的应用

摘要

Image distortion is a difficult problem in single grayscale specular images detection and removal method, so based on the mean field annealing algorithm a specular detection method of grayscale image is presented. The specular and diffuse reflection components are modeled by mean field annealing algorithm. Then, proportion of the specular and diffuse reflection components is estimated. Possible specular area is de-tected with proportion. Finally, the image restoration method based on BSCB model removals highlights. Experimental results show that the proposed method is effective. Compared with traditional highlight detection and recovery methods, this method can effectively detect grayscale image specular reflection area. The more the effect is restored in line with human vision, the better the image quality is recovered, thus the method improves the recovery rate of the image highlight areas.%为了解决单幅灰度图像高光去除方法恢复结果存在的图像失真问题,提出一种基于均场退火算法的单幅灰度图像高光检测方法.首先利用反射模型分别对镜面反射分量和漫反射分量的分布进行建模;然后通过均场退火算法的迭代过程估计镜面反射分量和漫反射分量的比例,对可能存在的高光区域进行检测;最后利用基于BSCB模型的图像修复方法修复高光区域.采用一种主观评价方法和客观评价方法相结合的性能的评价方法对文中方法进行验证,结果表明,该方法是有效的;与传统的高光检测与恢复的方法相比,该方法能够有效地检测出灰度图像中镜面反射区域,且恢复效果更符合人眼视觉、恢复后的图像质量更好,提高了图像高光区域的恢复率.