基于视觉注意机制的SAR图像小目标检测方法研究

项目名称： 基于视觉注意机制的SAR图像小目标检测方法研究

项目编号： No.41301449

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 天文学、地球科学

项目作者： 徐佳

作者单位： 河海大学

项目金额： 25万元

中文摘要： 对SAR图像中船只、飞机、汽车等人造目标进行自动检测在军事和民用领域均有重要的应用价值。然而,这类目标在图像中有效能量区域小且细节信息比较匮乏，现有方法在检测精度和效率方面均存在不足。本项目旨在将视觉注意的模型化计算引入SAR图像解译中，基于视觉注意机制构建一套高效稳健的小目标检测方案，为SAR图像目标检测研究提供新思路。根据SAR图像特征和小目标特点，研究模型化计算过程中涉及的特征选取、尺度选择、显著图生成、注意焦点选择等问题，设计出适用于SAR图像的视觉注意计算模型；针对大视场、强杂波、点目标等情况，借鉴变换域分析方法的优势提出改进措施；引入目标所处的上下文环境进行自顶向下的控制，研究上下文信息的描述方法及控制策略，构建融合双向注意机制的目标检测方法，实现复杂背景小目标检测。本研究有望推动SAR图像智能化信息处理的发展，并为军事目标搜索与监视、海上目标检测、智能交通等提供技术支持。

中文关键词： 合成孔径雷达；目标检测；小目标；视觉注意；特征选择

英文摘要： Automatic detection of man-made targets such as ships, planes and cars in SAR imagery is of much significance both in military and civil applications. However, these targets usually occupy a small portion of the image and lack of detailed feature information. Therefore, the existing methods suffer from inefficiency problems, characterized by a slow computation speed and a lack of accuracy when the image is large or the background is complex and cluttered. In this project, computational models of visual attention are introduced for interpreting SAR images and a new target detection method based on the visual attention mechanism is proposed for automatic detection of small targets in SAR images. According to features of SAR images and characteristics of small targets, this proposed project will be composed of three parts. The first part will focus on designing a SAR-suited visual attention model that solves challenges in feature extraction and selection, scale selection, saliency map generation, as well as focus selection and changing. The second part will focus on improving the proposed visual attention model by learning from the advantages of the spectral analysis models. And the last part will focus on using contextual information to refine target detection. Specifically, the description methods of contextual i

英文关键词： Synthetic Aperture Radar(SAR)；Target Detection；Small Target；Visual Attention；Feature Selection