Research on underwater target detection error compensation based on improved binocular vision.

A novel binocular vision error compensation method is proposed to solve the major error compensation problem caused by nonlinear distortion of camera and projector on underwater target detection. By optimizing the visual structure and integrating the projector with two cameras, the method enhances the adaptability and robustness of the system in the complex underwater environment. Through fine signal preprocessing such as multi-scale decomposition and feature extraction, the three-dimensional information of the target is captured more effectively and the data noise is effectively removed. The characteristics of underwater target detection error compensation data are extracted, and the characteristic parameters reflecting the significant difference between them are obtained. In order to ensure the accuracy of compensation results, a multi-scale attention mechanism is introduced into the improved binocular vision, and feature parameters are taken as the input of binocular vision model. After continuous learning and training, high-precision error compensation for underwater targets is realized. Experimental results show that different underwater targets can be detected when the average error value compensated by this method is less than 0.1 mm, and the maximum error value is always less than 1.5 mm. The structural similarity index measure of the proposed method is above 0.91, and the fluctuation is small. This method has significant advantages in reducing errors, adapting to different terrain targets, and providing stable and high-precision output, which shows its application potential and superiority in the field of underwater target detection, and provides a more effective and reliable technical solution for underwater target detection. [ABSTRACT FROM AUTHOR]