Research on the Application of Computer Data Analysis Technology in the Image Processing of Ocean Survey

Abstract

De-noising, enhancing, and edge extraction of ocean engineering images can improve the utilization of information. After bilateral filtering pre-processed the image, a multi-scale spatial representation is introduced, and finally an approximate sparse model iterative learning strategy is used to group and detect the candidate corner points set to select the corner points at the smallest scale as the best corner points. Experimental results show that the improved algorithm improves the corner detection rate and reduces the number of redundant corner points, which is better than the multi-scale Harris algorithm and Harris-Laplace algorithm.