IFRAD: A Fast Feature Descriptor for Remote Sensing Images
IFRAD: A Fast Feature Descriptor for Remote Sensing Images
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IFRAD：遥感图像的快速特征描述符
DOI：
10.3390/rs13183774
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发表时间：
2021-09-01
期刊：
影响因子：
5
通讯作者：
Xu, Wei
中科院分区：
文献类型：
--
作者：
Feng, Qinping;Tao, Shuping;Xu, Wei
特征描述是实现基于特征的遥感应用的必要过程。由于卫星平台资源有限，图像数据量大，特征提取作为特征匹配之前的一个过程，要求快速可靠。目前，最先进的特征描述方法是耗时的，因为它们需要根据周围的梯度或像素来定量地描述检测到的特征。在这里，我们提出了一种新的特征描述符，称为特征间相对方位角和距离（IFRAD），它将描述一个功能，根据其与图像中的其他功能。IFRAD算法在检测出一些FAST类特征后，首先根据标准选择一些稳定的特征，然后计算它们之间的关系，如相对距离和方位角，然后根据一定的规则描述它们之间的关系，使它们在保持一定仿射不变性的同时具有可区分性。最后，设计了一种特殊的特征相似度评估器，用于两幅图像中的特征匹配。与现有算法相比，该方法在合理降低尺度不变性的基础上，显著提高了计算效率。
Feature description is a necessary process for implementing feature-based remote sensing applications. Due to the limited resources in satellite platforms and the considerable amount of image data, feature description-which is a process before feature matching-has to be fast and reliable. Currently, the state-of-the-art feature description methods are time-consuming as they need to quantitatively describe the detected features according to the surrounding gradients or pixels. Here, we propose a novel feature descriptor called Inter-Feature Relative Azimuth and Distance (IFRAD), which will describe a feature according to its relation to other features in an image. The IFRAD will be utilized after detecting some FAST-alike features: it first selects some stable features according to criteria, then calculates their relationships, such as their relative distances and azimuths, followed by describing the relationships according to some regulations, making them distinguishable while keeping affine-invariance to some extent. Finally, a special feature-similarity evaluator is designed to match features in two images. Compared with other state-of-the-art algorithms, the proposed method has significant improvements in computational efficiency at the expense of reasonable reductions in scale invariance.