Spectral Clustering for Sonar Image Segmentation using Morphological Wavelet and Gray Level Transformation

摘要：

Spectral clustering algorithm has been used successfully in the domain of image processing except for sonar image segmentation. It cannot capture the sonar target accurately because the sonar image often has ambiguous object edge, extremely complex noisy background and critical shadow impact. In this paper, a new spectral clustering segmentation method base on morphological wavelet and gray level transformation was proposed. Firstly, a morphological midpoint wavelet which can do the image denoising effectively and make the object edge more clearly was constructed to enhance the sonar image; secondly, the gray level threshold transformation was used to remove the shadows of sonar image and the threshold was automatically obtained by the average iteration method; finally, constructed a new spectral clustering segmentation system for sonar image. The simulation experimental results demonstrate that the proposed method was more suitable for sonar image segmentation than the standard spectral clustering segmentation method.

关键词： spectral clustering:morphological wavelet gray level transformation:sonar image segmentation

作者: SHI Hong ZHAO Chun-hui SHEN Zheng-yan

作者单位: College of Information and Communication Engineering Harbin Engineering University Harbin,Heilongjia College of Underwater Acoustics Engineering Harbin Engineering University Harbin,Heilongjiang Provin

会议类型: 国际会议

会议名称: The 5th International Conference on Computer Science & Education(第五届国际计算机新技术与教育学术研讨会 ICCSE10)

会议地点: 合肥

会议语种:英文

页码: 1312-1316

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）