Sonar image interpretation and modelling

G. Russell, J. Bell, P. O. Holt, S. Clarke
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引用次数: 4

Abstract

The problem addressed is that of providing a model-based system to interpret sonar data from an autonomous or remotely controlled vehicle instrumentation, to aid navigation, improve sea floor mapping techniques, identify objects, simulate acoustic images for survey and analysis, or to aid the design of sonar systems. Analytic tools have been developed to segment and classify sea-bed and shallow seismic image textures, remove multiple reflections and detect objects on or close to the sea-bed. The sonar interpretation problem is placed within a model-based framework. Three dimensional surfaces are modelled to represent accurately natural seabed and sedimentary layers, so that the model parameters can provide a confident measure of the real data characteristics. Realistic synthetic sonar images are generated using the model-based simulation. In addition, new analytic tools can be developed and evaluated in a controlled experimental environment. This paper presents the conceptual sonar simulation system architecture, outlines the visualisation of the 3D sea floor model, describes the sonar system simulation and references image analysis tools available for texture segmentation and object detection.
声纳图像解释和建模
解决的问题是提供一个基于模型的系统来解释来自自主或远程控制车辆仪表的声纳数据,以辅助导航,改进海底测绘技术,识别物体,模拟用于调查和分析的声学图像,或辅助声纳系统的设计。分析工具已经开发出来,用于分割和分类海床和浅层地震图像纹理,去除多重反射和检测海床上或靠近海床的物体。声纳解释问题被置于一个基于模型的框架中。三维表面模型可以准确地表示自然海床和沉积层,因此模型参数可以提供真实数据特征的可靠度量。利用基于模型的仿真,生成了真实的合成声纳图像。此外,新的分析工具可以在受控的实验环境中开发和评估。本文介绍了概念声呐仿真系统架构,概述了三维海底模型的可视化,描述了声呐系统仿真,并参考了用于纹理分割和目标检测的图像分析工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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