【作者】 薛伟；

【导师】 王培康；

【作者基本信息】 中国科学技术大学 ， 通信与信息系统， 2010， 硕士

【摘要】 自动图像配准是以自动化的方式实现对图像的高精度、高效率配准的综合性图像处理技术。作为图像处理的核心技术,自动图像配准是图像融合、图像重建、三维建模等的关键性技术之一,在工业、军事、科研等领域有着广泛的应用前景和极高的应用价值。本文详细探讨了图像配准中几何变换模型、特征检测匹配算法以及模型参数估计算法。为了满足高精高效的要求,本文对SIFT算法和RANSAC算法都做了大量修改。但自动图像配准不是这些算法的简单组合应用,它有着完整的体系结构。从系统的角度出发,本文引入了图像多尺度分析技术和相关区域分析技术,提出了“自下而上,逐层迭代,逐步求精”的思想。图像多尺度分析消除了图像中的细节信息,使得检测匹配的特征点更加稳定。相关区域分析检测待配准图像间的重叠区域,逐层迭代时只检测相关区域,使得自动配准更高效。综合运用这些图像处理技术,形成了完整有机的自动图像配准的体系结构。仿真实验结果表明,本文提出的自动图像配准算法的估算参数精度高,误差小,基本不受待配准图像尺寸影响。分组实验表明,自动图像配准算法的运行时间较直接配准方法有了极大的改进,实现了算法的高效率。故本文研究的自动图像配准算法基本实现了自动化、高精度、高效率的三大要求。更多还原

【Abstract】 Automatic image registration is a comprehensive image processing technology that to achieve the high precision and high efficiency image registration automatically. As the core technology of image processing, automatic image registration is one of the key methods in image fusion, image reconstruction, 3D modeling. And it has wide application and high value n the industrial, military, scientific research.This paper discusses the geometric transformation model, feature detection and matching algorithms, and model parameter estimation algorithm in detail. In order to meet the requirements of high precision and efficient, SIFT algorithm and RANSAC algorithm have been changed a lot. But automatic image registration is not the simple combination of these algorithms; it has a complete architecture of itself. From the view of system, this paper introduces the image multiscale analysis technology and related areas analysis technology, proposed method of "bottom to up, layer by layer, step by step". Image multiscale analysis eliminates the image details, and let image feature points be more stable. Related areas analysis detects overlap areas between images, and makes automatic registration be more efficient. Automatic image registration forms a complete organic architecture by combination of these image processing techniques.Simulation results show that the proposed automatic image registration algorithm in this paper can estimate parameters in high precision, small error, and can’t affect by the image size. Compared by direct registration method, Group results show that automatic image registration algorithm has been greatly improved, achieved high efficiency. Therefore, this paper’s automatic image registration algorithm achieves three requirements of automated, high precision and high efficiency.更多还原