A Review of Sonar Image Segmentation for Underwater Small Targets

Yuanyuan Tian, Luyu Lan, Linna Sun
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引用次数: 4

Abstract

The existing image segmentation methods are various, but due to the particularity of sonar images, the ordinary image segmentation methods often fail to achieve ideal results when processing sonar images and have limitations. On the basis of studying a large number of image segmentation methods at home and abroad, the authors recommends the following methods with comprehensive characteristics that are more suitable for sonar image segmentation, such as thresholding, edge detection, MRF and clustering algorithm. For nearly a decade, many scholars have improved the traditional segmentation methods by combining the characteristics of sonar images, or improved the algorithms by combining various segmentation methods to make up for the shortcomings of the original segmentation methods applied to sonar images.
水下小目标声纳图像分割研究进展
现有的图像分割方法多种多样,但由于声纳图像的特殊性,普通的图像分割方法在处理声纳图像时往往达不到理想的效果,存在局限性。在对国内外大量图像分割方法进行研究的基础上,笔者推荐了阈值分割、边缘检测、MRF和聚类算法等具有综合特点的更适合于声纳图像分割的方法。近十年来,许多学者结合声纳图像的特点,对传统的分割方法进行了改进,或者结合各种分割方法对算法进行了改进,以弥补原有分割方法应用于声纳图像的不足。
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