高级检索

快自旋小天体跨尺度光照不变匹配算法

Fast Spin Cross-Scale Small-Body Light Invariant Matching Algorithm

  • 摘要: 小天体探测器附着过程中,图像存在尺度、视角和光照变化,传统特征匹配算法难以获得精准匹配。提出一种小天体跨尺度光照不变匹配算法。针对附着过程中图像存在尺度变化的问题,将全局注意力机制与空洞卷积相结合,构建尺度自适应调整模块;设计视角不变特征提取模块解决特征匹配算法大视角变化下匹配正确率低的问题;结合自注意力机制与互注意力机制建立特征依赖关系,提取光照不变特征。利用谷神星及贝努的真实图像分别进行了实验验证,结果表明,本文所提出算法在大尺度、视角及光照变化下,特征匹配准确率达89%以上。

     

    Abstract: During the attachment process of small body spacecraft, there are scale, viewpoint and illumination variations in the image, making it difficult for traditional feature-matching algorithms to obtain accurate matches. In this paper, a small-body cross-scale illumination invariant matching algorithm is proposed. To address the problem of scale changes in the image during the attachment process, the global attention mechanism is combined with the dilated convolution to construct a scale adaptive adjustment module; the viewpoint invariant feature extraction module is designed to solve the problem of low matching accuracy under the large viewpoint changes in the feature matching algorithm; the self-attention mechanism is combined with the inter-attention mechanism to establish the feature dependency relationship, and the illumination invariant features are extracted. Experimental validation is carried out using the real images of Ceres and Bennu, and the results show that the proposed algorithm achieves an accuracy of more than 89% under large scale, view angle and illumination changes.

     

/

返回文章
返回