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基于内容的光学遥感图像检索关键技术研究

Research on Key Techniques of Content-Based Optical Remote Sensing Image Retrieval

【作者】 张男

【导师】 郁文贤; 粟毅;

【作者基本信息】 国防科学技术大学 , 信息与通信工程, 2008, 博士

【摘要】 遥感图像数据作为数字地球等各项重大计划建设中的基础数据,其快速浏览和高效检索是遥感图像信息提取和共享的重要手段;基于内容的图像检索技术作为从试图理解图像内容的角度有效管理和利用图像数据库中信息的手段,己经成为图像数据库、计算机视觉等领域的研究热点和未来信息高速公路、数字图书馆等重大项目中的关键技术,为解决大型遥感图像数据库的信息提取难题提供了新的契机。然而,遥感图像数据的多样性、复杂性和海量性无疑对基于内容的遥感图像库检索提出了巨大的挑战。基于内容的遥感图像库检索技术是遥感图像处理、图像数据库技术、计算机视觉、模式识别等领域相结合的国际前沿课题,对于促进遥感图像信息的提取和共享,具有十分重要的理论意义和实用价值。本文旨在针对基于内容的光学遥感图像库检索的关键技术,提出一些创新性思路和方法,并分别从理论和技术的角度对其价值和实用性予以分析和验证。主要贡献及创新点可概括如下:1、提出一个基于MPEG-7标准的遥感图像模型,并在此模型框架下,针对遥感图像的检索流程,定义了一系列的运算,完整地实现了对遥感图像检索的描述。2、提出了遥感图像检索领域纹理特征适应性的评估方法,针对不同分辨程度、不同地貌特征的遥感图像,利用检索的查全、查准率性能分析方法研究了5种常用纹理特征提取方法的适应程度,并对其计算复杂性进行了比较。3、提出了一种针对遥感图像检索的交互式遗传检索方法,根据遥感图像特点设计了染色体编码方法和遗传操作过程;充分地实现了人机交互和计算机遗传算法的有效结合。4、提出了一种支持遥感图像检索的基于多带小波的迭代分形压缩算法,通过实验对其可行性和有效性进行了验证。5、根据论文的研究成果,设计并实现了一个基于内容的遥感图像检索实验系统。该系统能够实现常规的基于内容的光学遥感图像检索的功能,同时还能利用交互式遗传算法实现一般意义上的人机交互。

【Abstract】 Remote Sensing Data are basic data in digital earth project. Their quick browsing and efficient retrieval are important for the extraction and sharing of remote sensing information. As an efficient means for the management and utilization of the imformation in image database from the viewpoint of comprehension of image content, the content-based image retrieval (CBIR) technique has become one of the most active research points in image databases, computer vision etc. And the CBIR technique has been a key technique for information highway and digital library projects. CBIR also provides a new chance to solve the problem of information extraction from large remote sensing image database. However, the diversity and complexity of remote sensing images and the enormous data volume bring big challenges for the effective retrival of imformation from remote sensing image databases. Content-based retrieval of remote sensing database is a hot topic by integrating multiple disciplines including remote sensing image processing, image databases, computer vision and pattern recognition etc. and has gotten international considerations. Therefore, researches on it have important meanings in theory and practice for promoting remote sensing information acquisition and sharing.This dissertation proposes some new ideas and methods on key techniques for the content-based retrieval of optical remote sensing image database. The efficiency and practicability of these new methods are validated through theoretical analysis and simulations. The main work and innovations can be concluded in five aspects as given bellow:1. A retrieval model for remote sensing images is constructed, which is based on the MPEG-7 standard. Using this new model, a seires of operations are introduced to describe the retrieval process of remote sensing images perfectly.2. An evaluation method for the adaptability of texture features in remote semsing image retrieval is proposed. The adaptabilities for five commonly used texture features extraction methods are investigated by analyzing the index rates and precisions for various remote sensing images with different resolutions and physiognomies. The calculation complexities of these five methods are compared.3. An interactive genetic retrieval method is proposed. The chromosome coding and the genetic operations are special designed by using the characteristics of remote sensing images. The new method exhibits the combination of human computer iteraction and genetic algorithm effectively. 4. An interative fractal image compression method based on muti-band wavelet transformation is proposed. Simulations show the efficiency of the new method.5. According to the achievements above, an experimental system for the CBIR of remte sensing images is designed and implemented. The system can carry out conventional CBORSIR and can also implement human-machine interaction by interactive genetic algorithm.

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