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CHAIR: automatic image registration based on correlation and Hough transform

机译:主席:基于相关性和霍夫变换的自动图像配准

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Automatic image registration is a process related to several application fields: remote sensing, medicine and computer vision, among others. Particularly in the field of remote sensing, the ever-increasing number of available satellite images requires automatic image registration methods, capable of correctly aligning a new image. An automatic image registration method - CHAIR (correlation- and Hough transform-based method of automatic image registration) - is proposed, the key concept of which relies on the ‘correlation image’ produced in both the horizontal and vertical directions. In particular, the computation of the distance of an identified diagonal brighter strip in the correlation image (through the Hough transform) to an offset (the main diagonal) allows for the determination of translational shifts and consequently control points. The set of obtained control points allows for the correction of several types of distortions. The geometric correction quality achieved by CHAIR was objectively evaluated through measures recently proposed, which allow for a more complete assessment of the obtained results. The CHAIR performance was evaluated on both synthetic and real data, with different spatial resolutions and spectral contents. CHAIR has been shown to be able to correctly align two images with a subpixel accuracy, having a priori a ‘gold standard’ image covering a considerable part of the image to be registered, and has also been shown to work for images of different sensors and/or different spectral bands, situations where traditional correlation methods often yield low and smooth peaks on the correlation surface. It is also able to account for elevation differences and to some extent for rotation and scale effects. Furthermore, it has been shown to have potential for registering synthetic aperture radar (SAR) with optical images.View full textDownload full textRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/01431161.2012.701345
机译:自动图像配准是与多个应用领域相关的过程:遥感,医学和计算机视觉等。特别是在遥感领域,可用卫星图像的数量不断增加,需要能够正确对齐新图像的自动图像配准方法。提出了一种自动图像配准方法CHAIR(基于相关和霍夫变换的自动图像配准方法),其关键概念依赖于在水平和垂直方向上产生的“相关图像”。特别地,相关图像中所识别的对角较亮条的距离(通过霍夫变换)到偏移量(主对角线)的距离的计算允许确定平移和控制点。所获得的控制点的集合允许校正几种类型的失真。通过最近提出的措施,客观地评估了CHAIR所达到的几何校正质量,从而可以对获得的结果进行更完整的评估。在具有不同空间分辨率和光谱内容的合成数据和真实数据上均评估了CHAIR的性能。事实证明,CHAIR能够以亚像素精度正确对齐两幅图像,其先验的“金标准”图像覆盖了要配准的图像的相当一部分,并且还显示出可用于不同的传感器和/或不同的光谱带,传统的相关方法通常会在相关表面上产生低而平滑的峰的情况。它也能够解决高程差异,并在某种程度上解决旋转和比例效应。此外,它已显示出可以将合成孔径雷达(SAR)与光学图像配准的潜力。 Delicious,linkedin,facebook,stumbleupon,digg,google,更多”,发布号:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/01431161.2012.701345

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