Conversion of underwater concrete images to air in detection of hydraulic structures


 Detection of apparent concrete defects in hydraulic buildings is an important measure to ensure their safe and stable operation. When the optical camera is fixed in a waterproof housing for underwater concrete surface defect detection, the dark scenes and refraction of light on different media surfaces result in poor image quality and accompanying refractive distortion. In order to make the collected underwater image data better applied to underwater concrete inspection, we propose an equivalent air image conversion method that combines underwater image color enhancement and refractive distortion correction. This paper, proposes 2 models for underwater image-to-air conversion, one of which, using the light projection method, establishes a refractive distortion model for camera received light penetrating a multilayer medium underwater for correcting the refractive distortion of underwater images and the conversion of image field of view (FOV), and the other, by analyzing the problem of low image imaging quality and loss of edge information due to underwater uneven illumination environment, proposes a dark channel priority adaptive enhancement algorithm for improving underwater image quality. The experimental results in real scenes show that the imaging quality of underwater images is improved by converting underwater images into the air. The pixel error of images converted into the air is ≤1 pixel, and the FOV error of images is ≤8.5%. High precision underwater image conversion provides strong support for subsequent underwater measurement.