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首页> 外文期刊>Frontiers of computer science in China >Applying rotation-invariant star descriptor to deep-sky image registration
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Applying rotation-invariant star descriptor to deep-sky image registration

机译：将旋转不变恒星描述符应用于深空图像配准

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摘要

Image registration is a critical process of many deep-sky image processing applications. Image registration methods include image stacking to reduce noise or achieve long exposure effects within a short exposure time, image stitching to extend the field of view, and atmospheric turbulence removal. The most widely used method for deep-sky image registration is the triangle- or polygon-based method, which is both memory and computation intensive. Deep-sky image registration mainly focuses on translation and rotation caused by the vibration of imaging devices and the Earth's rotation, where rotation is the more difficult problem. For this problem, the best method is to find corresponding rotation-invariant features between different images. In this paper, we analyze the defects introduced by applying rotation-invariant feature descriptors to deep-sky image registration and propose a novel descriptor. First, a dominant orientation is estimated from the geometrical relationships between a described star and two neighboring stable stars. An adaptive speeded-up robust features (SURF) descriptor is then constructed. During the construction of SURF, the local patch size adaptively changes based on the described star size. Finally, the proposed descriptor is formed by fusing star properties, geometrical relationships, and the adaptive SURF. Extensive experiments demonstrate that the proposed descriptor successfully addresses the gap resulting from applying the traditional feature-based method to deep-sky image registration and performs well compared to state-of-the-art descriptors.
机译：图像配准是许多深空图像处理应用程序的关键过程。图像配准方法包括：图像堆叠以减少噪声或在短时间内获得长时间曝光效果；图像拼接以扩展视野；以及消除大气湍流。用于深空图像配准的最广泛使用的方法是基于三角形或多边形的方法，该方法既占用内存又需要大量计算。深空图像配准主要关注由成像设备的振动和地球自转引起的平移和自转，其中自转是更困难的问题。对于此问题，最好的方法是在不同图像之间找到相应的旋转不变特征。在本文中，我们分析了将旋转不变特征描述符应用于深空图像配准所引入的缺陷，并提出了一种新颖的描述符。首先，从描述的恒星和两个相邻的稳定恒星之间的几何关系估计主导方向。然后，构建自适应加速鲁棒特征（SURF）描述符。在SURF的构建过程中，局部补丁大小会根据所描述的星形大小自适应地更改。最后，通过融合恒星特性，几何关系和自适应SURF来形成所提出的描述符。大量实验表明，所提出的描述符成功地解决了将传统的基于特征的方法应用于深空图像配准所产生的空白，并且与最新的描述符相比性能良好。

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