Qin Guodong, Zhang Haoran, Cheng Yong, Xu Youzhi, Wang Feng, Liu Shijie, Qin Xiaoyan, Zhao Ruijuan, Zuo Congju, Ji Aihong
Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031, China.
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing 210016, China.
Sensors (Basel). 2024 Sep 26;24(19):6227. doi: 10.3390/s24196227.
This paper addresses image enhancement and 3D reconstruction techniques for dim scenes inside the vacuum chamber of a nuclear fusion reactor. First, an improved multi-scale Retinex low-light image enhancement algorithm with adaptive weights is designed. It can recover image detail information that is not visible in low-light environments, maintaining image clarity and contrast for easy observation. Second, according to the actual needs of target plate defect detection and 3D reconstruction inside the vacuum chamber, a defect reconstruction algorithm based on photometric stereo vision is proposed. To optimize the position of the light source, a light source illumination profile simulation system is designed in this paper to provide an optimized light array for crack detection inside vacuum chambers without the need for extensive experimental testing. Finally, a robotic platform mounted with a binocular stereo-vision camera is constructed and image enhancement and defect reconstruction experiments are performed separately. The results show that the above method can broaden the gray level of low-illumination images and improve the brightness value and contrast. The maximum depth error is less than 24.0% and the maximum width error is less than 15.3%, which achieves the goal of detecting and reconstructing the defects inside the vacuum chamber.
本文探讨了核聚变反应堆真空室内昏暗场景的图像增强和三维重建技术。首先，设计了一种改进的带自适应权重的多尺度视网膜低光图像增强算法。它能够恢复在低光环境中不可见的图像细节信息，保持图像清晰度和对比度以便于观察。其次，根据真空室内目标板缺陷检测和三维重建的实际需求，提出了一种基于光度立体视觉的缺陷重建算法。为了优化光源位置，本文设计了一个光源照明轮廓模拟系统，无需进行大量实验测试即可为真空室内的裂纹检测提供优化的光阵列。最后，构建了一个搭载双目立体视觉相机的机器人平台，并分别进行了图像增强和缺陷重建实验。结果表明，上述方法可以拓宽低照度图像的灰度级，提高亮度值和对比度。最大深度误差小于24.0%，最大宽度误差小于15.3%，实现了真空室内缺陷检测和重建的目标。
