Enhancing the Quality of Low-Light Printed Circuit Board Images through Hue, Saturation, and Value Channel Processing and Improved Multi-Scale Retinex  

作　　者：Huichao Shang Penglei Li Xiangqian Peng Huichao Shang;Penglei Li;Xiangqian Peng(School of Mechanical and Electrical Engineering, Zhongyuan University of Technology, Zhengzhou, China;School of Mechanical and Electrical Engineering, Hunan University of Science and Technology, Xiangtan, China)

机构地区：[1]School of Mechanical and Electrical Engineering, Zhongyuan University of Technology, Zhengzhou, China [2]School of Mechanical and Electrical Engineering, Hunan University of Science and Technology, Xiangtan, China

出　　处：《Journal of Computer and Communications》2024年第1期1-10,共10页电脑和通信（英文）

摘　　要：To address the issue of deteriorated PCB image quality in the quality inspection process due to insufficient or uneven lighting, we proposed an image enhancement fusion algorithm based on different color spaces. Firstly, an improved MSRCR method was employed for brightness enhancement of the original image. Next, the color space of the original image was transformed from RGB to HSV, followed by processing the S-channel image using bilateral filtering and contrast stretching algorithms. The V-channel image was subjected to brightness enhancement using adaptive Gamma and CLAHE algorithms. Subsequently, the processed image was transformed back to the RGB color space from HSV. Finally, the images processed by the two algorithms were fused to create a new RGB image, and color restoration was performed on the fused image. Comparative experiments with other methods indicated that the contrast of the image was optimized, texture features were more abundantly preserved, brightness levels were significantly improved, and color distortion was prevented effectively, thus enhancing the quality of low-lit PCB images.To address the issue of deteriorated PCB image quality in the quality inspection process due to insufficient or uneven lighting, we proposed an image enhancement fusion algorithm based on different color spaces. Firstly, an improved MSRCR method was employed for brightness enhancement of the original image. Next, the color space of the original image was transformed from RGB to HSV, followed by processing the S-channel image using bilateral filtering and contrast stretching algorithms. The V-channel image was subjected to brightness enhancement using adaptive Gamma and CLAHE algorithms. Subsequently, the processed image was transformed back to the RGB color space from HSV. Finally, the images processed by the two algorithms were fused to create a new RGB image, and color restoration was performed on the fused image. Comparative experiments with other methods indicated that the contrast of the image was optimized, texture features were more abundantly preserved, brightness levels were significantly improved, and color distortion was prevented effectively, thus enhancing the quality of low-lit PCB images.

关 键 词：Low-Lit PCB Images Spatial Transformation Image Enhancement Image Fusion HSV 

分 类 号：X70[环境科学与工程—环境工程]