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A novel multistage image registration technique with graph-based region descriptors.

机译：一种新颖的具有基于图的区域描述符的多级图像配准技术。

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摘要

Successful image alignment is an essential function for many image processing methods. The geometric and photometric variations between images adversely affect the ability for an algorithm to estimate the transformation parameters that relate the two images. Local deformations, lightning conditions, object obstructions, and perspective differences all contribute to the challenges faced by traditional registration techniques. In this work, a novel multistage registration approach is proposed that is resilient to view point differences, image content variations, and lighting conditions. The proposed method is demonstrated to be effective for registration scenarios involving images of a scene or object before and after a disaster. Robust registration is realized through the utilization of a novel region descriptor which couples the spatial and textural characteristics of invariant feature points. Clusters of invariant feature points are shown to provide more discriminative features than the traditional point descriptors.;The multistage method is a hierarchy of registration approaches that takes advantage of feature, intensity and Fourier-based techniques. The three phases include a limited search window method that employs the proposed graph-based region descriptor, a comprehensive approach which fuses intensity and feature-based analysis, and an exhaustive search method which also utilizes the region descriptor. Each successive stage of the registration technique is evaluated through an effective similarity metric which determines subsequent action. The registration of aerial and street view images from pre and post disaster provide strong evidence that the proposed method estimates more accurate global transformation parameters than traditional intensity and feature-based methods. Experimental results involving the mutual information metric confirm the robustness and accuracy of the proposed multistage image registration methodology. Moreover, experimental results show that the proposed graph-based region descriptor offers higher matching accuracy than SIFT, SURF and BRISK descriptors for the test set of images from before and after a disaster.
机译：成功的图像对齐是许多图像处理方法的基本功能。图像之间的几何和光度变化会对算法估计与两个图像相关的变换参数的能力产生不利影响。局部变形，雷电条件，物体障碍和视角差异都加剧了传统套准技术所面临的挑战。在这项工作中，提出了一种新颖的多阶段配准方法，该方法可以抵抗视点差异，图像内容变化和照明条件。实践证明，所提出的方法对于涉及灾难前后场景或物体图像的配准方案是有效的。通过利用新颖的区域描述符实现了稳健的配准，该描述符结合了不变特征点的空间和纹理特征。与传统的点描述符相比，不变特征点的聚类显示出更多的判别性特征。多级方法是利用特征，强度和基于傅立叶技术的配准方法的层次结构。这三个阶段包括采用建议的基于图形的区域描述符的有限搜索窗口方法，融合强度和基于特征的分析的综合方法以及还利用区域描述符的详尽搜索方法。通过确定后续动作的有效相似性度量来评估配准技术的每个连续阶段。记录灾前和灾后的鸟瞰图和街景图像提供了有力的证据，表明与传统的基于强度和特征的方法相比，该方法可估算出更准确的全局转换参数。涉及互信息量度的实验结果证实了所提出的多级图像配准方法的鲁棒性和准确性。此外，实验结果表明，针对灾难前后的图像测试集，所提出的基于图的区域描述符比SIFT，SURF和BRISK描述符具有更高的匹配精度。

著录项

  • 作者

    Bowen, Francis.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 193 p.
  • 总页数 193
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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