A Study On Object Segmentation Method Of Underwater Strong Noise Image

As we all know, the image segmentation technology has played a very important role in the field of people’s lives, and it exists around us. In recent years, with the development of the maritime domain, image segmentation technology is increasingly used in the segmentation of underwater strong noise image targets. And the situation of underwater strong noise image’s object segmentation will affect the understanding and analysis of underwater image information. Then, it will affect the development and utilization of the marine. Therefore, underwater strong noise image object segmentation technology has received considerable attentions, and it has become a popular field of digital image processing research topics. As the special underwater environment makes the underwater image contains strong noise, we can hardly make judgments of the underwater specific circumstances. This article is mainly targeted at the research of underwater strong noise image object segmentation processing, and the use of underwater noise image associated with strong image segmentation algorithm for object segmentation, removal of the original underwater strong noise in the image, to be able to demonstrate underwater strong noise in the target image detail effect, highlighting the underwater strong noise characteristics of the target image. We compare the results of the different algorithms for underwater strong noise image and conclude the advantages and disadvantages. At last, we use the VC++to simulate and process in the Gaussian white noise and the Salt-Pepper noise, and we achieve the desired pre-process effect.