College of Computer Science and Technology, Xi'an University of Science and Technology
College of Mechanical Engineering, Xi'an University of Science and Technology

煤矿井下图像存在较严重的光照不均匀和噪声干扰，现有基于Retinex的方法直接应用于煤矿井下图像增强易出现光晕伪影、边缘模糊、过增强和噪声放大等问题。针对上述问题，提出了一种基于多尺度梯度域引导滤波的煤矿井下图像增强方法。首先，将多尺度思想引入梯度域引导滤波中，实现对非均匀光照的准确估计，有效解决了增强图像时光晕伪影及边缘模糊的问题。然后，利用Retinex模型分离出光照分量和反射分量：对于光照分量，通过自适应伽马校正函数逐像素地修正光照信息，实现对图像暗区域增强的同时，抑制亮区域过增强，并使用限制对比度自适应直方图均衡化方法调整图像对比度；对于反射分量，将梯度域引导滤波与多尺度细节提升相结合，在准确去除噪声后提升纹理细节，避免了增强图像时噪声放大的问题。最后，将处理后的光照分量及反射分量融合，计算图像增益系数，并使用线性色彩恢复方法实现对原始RGB图像的逐像素增强，提升方法处理效率。实验结果表明，从主客观角度与现有方法相比，经所提方法处理后的图像在色彩保持、对比度、噪声抑制、细节保留等方面均取得了较好的增强效果，同时处理效率较高。

There are serious issues with uneven lighting and noise interference in coal mine underground images. The existing Retinex based methods are directly applied to enhance coal mine underground images, which are prone to problems such as halo artifacts, blurred edges, over enhancement, and noise amplification. In order to solve the above problems, a coal mine underground image enhancement method based on multi-scale gradient domain guided image filtering is proposed. Firstly, the multi-scale idea is introduced into gradient domain guided image filtering to achieve accurate estimation of non-uniform lighting, effectively solving the problems of halo artifacts and edge blurring in enhanced images. Secondly, the Retinex model is used to separate the lighting component and reflection component. For the lighting component, the lighting information is corrected pixel by pixel through an adaptive gamma correction function, which enhances the dark areas of the image while suppressing the over enhancement of the bright areas. The image contrast is adjusted using a contrast limited adaptive histogram equalization method. For the reflection component, gradient domain guided image filtering is combined with multi-scale detail enhancement to accurately remove noise and improve texture details, avoiding the problem of noise amplification during image enhancement. Finally, the processed lighting and reflection components are fused, and the image gain coefficient is calculated. The linear color restoration method is used to enhance the original RGB image pixel by pixel, improving the processing efficiency of the method. The experimental results show that, from a subjective and objective perspective, compared with existing methods, the images processed by the proposed method have achieved better enhancement effects in color preservation, contrast, noise suppression, detail preservation, and other aspects, while also having higher processing efficiency.

国家重点研发计划资助项目（2022YFB3304401）。

牟琦，葛相甫，王新月，等. 基于多尺度梯度域引导滤波的煤矿井下图像增强方法[J]. 工矿自动化，2024，50（6）：79-88, 111.

MU Qi, GE Xiangfu, WANG Xinyue, et al. A coal mine underground image enhancement method based on multi-scale gradient domain guided image filtering[J]. Journal of Mine Automation，2024，50（6）：79-88, 111.