基于两步哈里斯-拉普拉斯检测器和SIFT描述符的高分辨率图像配准

Kratika Sharma, Ajay Goyal
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引用次数: 3

摘要

目前,大尺寸甚高分辨率(VHR)图像的配准是远程图像分析的重要课题之一。然而,到目前为止,仍然很少找到一种准确、鲁棒的图像配准方法,现有的方法大多是针对小尺寸图像设计的。目前最常用的配准方法中,SIFT配准效果较好,但计算速度较慢。为了克服这个困难,提出了从粗到精的策略和并行实现,但这再次增加了多台pc的额外开销。本文提出了一种将Harris-Laplace检测器与SIFT描述子相结合的粗变细策略。该方法首先对图像进行粗略配准,然后将大尺寸图像分割成小尺寸的可处理块进行精细配准。它通过提供更高的匹配率来提高配准精度,并且无需多台pc就可以快速计算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Very high resolution image registration based on two step Harris-Laplace detector and SIFT descriptor
At present, registration of the Large size Very High Resolution (VHR) images is one of the important task in remote image analysis. However, until now, it is still rare to find an accurate and robust image registration method, and most of the existing methods are designed for small size images. Among the most popular methods, SIFT is performed well to register VHR images but the calculation procedure is too slow. To overcome this difficulty coarse-to-fine strategy and parallel implementation have been proposed but again this increased the extra overhead of multiple PCs. This paper proposes a coarse-to-fine strategy, that combine Harris-Laplace detector together with SIFT descriptor. Proposed approach starts with roughly register the image at first place and then to perform fine registration by dividing the large size image in to small size process-able blocks. It improves registration accuracy by providing increased matching ratio as well as makes computation fast without the need of multiple PCs.
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