Optical camera communications (OCC) has been growing rapidly in recent years, which offers a flexible and low-cost way to achieve underwater wireless optical communication (UWOC). However, the existence of underwater bubbles and suspended impurities will greatly decrease the signal quality. In this paper, we propose a de-bubble algorithm and a sampling scheme based on binary fringes correction (BFC) to enhance the communication quality. The experimental results demonstrate that a robust transmission can be achieved in the harsh bubble environment by applying the proposed two algorithms.

The traditional level set algorithm selects the position of the initial contour randomly and lacks the processing of edge information. Therefore, it cannot accurately extract the edge of the brain tissue. In order to solve this problem, this paper proposes a level set algorithm that fuses partition and Canny function. Firstly, the idea of partition is fused, and the initial contour position is selected by combining the morphological information of each region, so that the initial contour contains more brain tissue regions, and the efficiency of brain tissue extraction is improved. Secondly, the canny operator is fused in the energy functional, which improves the accuracy of edge detection of rhesus monkey brain tissue while retaining the advantage of the traditional level set algorithm in processing an uneven gray image. Experimental results show that the algorithm can accurately extract the brain tissue of rhesus monkeys with an accuracy of up to 86%.