厦门大学学报（自然科学版）2018，Vol.57Issue(3)：390-395,6.DOI:10.6043/j.issn.0438-0479.201708005
侧扫声呐图像噪声模型的分析
Analysis of Side-scan Sonar Image Noise Model
摘要
Abstract
Side-scan sonar image contain speckle noises due to their characteristics of imaging mechanism and complicated seabed en-vironment in the acquisition process.Seabed reverberations of different types of substrates often exert different effects on lateral-scan sonar imaging.Based on the analysis of the seabed reverberation statistical model,the optimal fitting distribution model is obtained under five typical probability distribution models and the evaluation based on two eigenvalues is proposed after analyzing the charac-teristic parameters of gray histogram.Finally,the noise model of side-scan sonar image and image classification of different sediment types were achieved by multiple regression model analyses.Experimental results show that Gamma distribution model enjoys the ad-vantages of accurate fitting characteristics and convenient calculation of probability.According to model parameters and image fea-tures,the model can effectively simulate the noise caused by different sediment types of reverberation,and is conducive to the classifi-cation of the sediment and the elimination of noise.关键词
海底混响/概率分布/声呐图像/底质分类/多元回归Key words
seabed reverberation/probability distributions/sonar image/sediment classification/multiple regression分类
信息技术与安全科学引用本文复制引用
张楷涵,袁飞,程恩..侧扫声呐图像噪声模型的分析[J].厦门大学学报（自然科学版）,2018,57(3):390-395,6.基金项目
国家自然科学基金(61471308,61571377) （61471308,61571377）
