Specular Reflection Image Enhancement Based on a Dark Channel Prior
Specular Reflection Image Enhancement Based on a Dark Channel Prior
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DOI：
10.1109/jphot.2021.3053906
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发表时间：
2021-02
影响因子：
2.4
通讯作者：
Ye Xin;Zhenhong Jia;Jie Yang;N. Kasabov
中科院分区：
文献类型：
--
作者：
Ye Xin;Zhenhong Jia;Jie Yang;N. Kasabov
针对真实的场景中高光图像信息丢失的问题，提出了一种基于暗通道先验的高光图像增强算法。该算法首先基于暗通道先验算法，采用移动窗口最小滤波器估计全局光照分量。然后，引入基于局部像素色差的加权函数来解决图像中的光晕伪影。然后，采用改进的引导滤波算法对透射率进行优化，提高了算法的计算效率。最后，通过CLAHE算法调整图像的亮度，增强图像的局部细节。实验结果表明，该方法能有效地增强镜面高光图像中的信息，其处理效果明显优于其他算法。
In this paper, we propose a specular highlight image enhancement algorithm based on a dark channel prior to solve the problem of information loss in specular highlight images in real scenes. First, the algorithm is based on the dark channel prior algorithm, and a moving window minimum filter is used to estimate the global illumination component. Then, a weighted function based on the local pixel color difference is introduced to solve the halo artifacts in the image. Then, the improved guided filter algorithm is used to optimize the transmittance, which improves the computational efficiency of the algorithm. Finally, the brightness of the image is adjusted by the CLAHE algorithm to enhance the local details of the image. Experimental results show that this method can effectively enhance the information in specular highlight images, and its processing results are obviously better than those of other algorithms.