关键词: 侧扫声纳图像, 二维经验模态分解, 水平集, 能量函数

Abstract: Characteristics of different regions in side scan sonar imagery are analyzed. A kind of improved BEMD-multilayer level set segmentation algorithm is proposed to segment sonar imagery into three categories of region. In order to improve the accuracy of segmentation and the convergence rate of the level set model, BEMD（Two-dimensional Empirical Mode Decomposition） is used to describe the model's energy function. Through BEMD weighted parameters, the anti-noise performance of the model is improved without losing the accuracy of segmentation. After analysis of the contact of the c-means algorithm and the level set algorithm, an improved c-means algorithm is used to initialize the level set evolution curve. What’s more, a penalty term in the energy of level set is added to improve the evolution speed. Unsupervised sonar image segmentation experiments are done by using improved BEMD-hierarchical level set segmentation algorithm. Compared with other algorithms, the noise immunity, the segmentation accuracy and rapidity of the proposed algorithm are validated.

Key words: side scan sonar imagery, Two-dimensional Empirical Mode Decomposition（BEMD）, level set, energy function