基于HSV空间的煤矿井下低光照图像增强方法

An Algorithm for Low-Light Image Enhancement in Coal Mines Based on HSV Space

针对煤矿井下采集到的图像对比度低、光照不均和细节信息弱等问题,提出一种基于色相-饱和度-明度(Hue-Saturation-Value,HSV)颜色空间的煤矿井下低光照图像增强方法。该方法基于图像的HSV空间,通过对低光照图像的亮度通道V通道的主要结构和边缘细节分别进行对比度增强,这样可以更好地抑制图像细节丢失,同时可以较好地再现原图中的轮廓和纹理细节。首先,将输入的煤矿井下低光照图像转换到HSV空间,利用相对全变分滤波(RTV)与改进的边窗滤波(SWF),分别对提取的V通道图像进行主要结构提取和轮廓边缘保留,对其非线性灰度拉伸后利用主成分分析融合技术(PCA)重构V通道图像,即融合V通道图像的主要结构和精细结构,最后合成图像,完成图像增强。通过实验验证,提出的基于HSV空间的煤矿井下低光照图像增强方法,在色彩和边缘模糊处理等方面表现良好,在煤矿井下工作面等环境中,对图像进行定量和定性实验,结果表明,与6种方法相比,增强图像的对比度、自然度和图像细节方面表现更好。

A low light image enhancement method based on HSV space is proposed to address the issues of low contrast,uneven lighting,and weak detail information in images collected underground in coal mines.This method is based on the Hue-Saturation-Luminance(HSV)color space of the image,and enhances the contrast of the main structure and edge details of the brightness channel V channel in low light images.This can better suppress image detail loss and reproduce the contour and texture details in the original image.Firstly,the input low light image of the coal mine underground is converted into HSV space,and the main structure and contour edges of the extracted V-channel image are extracted and preserved using relative total variation filtering(RTV)and improved side window filtering(SWF).After nonlinear grayscale stretching,principal component analysis fusion technology(PCA)is used to reconstruct the V-channel image,which fuses the main structure and fine structure of the V-channel image.Finally,the image is synthesized,Complete image enhancement.Through experimental verification,the proposed low light image enhancement method for coal mine underground based on HSV space performs well in color and edge blur processing.Quantitative and qualitative experiments were conducted on images in environments such as coal mine underground working faces.The results show that compared with the six algorithms,the proposed method performs better in improving image contrast,enhancing image naturalness,and restoring image details.