SAR image matching algorithm based on multi-class features
Not on the map. Why?
Abstract (arXiv)
Synthetic aperture radar has the ability to work 24/7 and 24/7, and has high application value. Propose a new SAR image matching algorithm based on multi class features, mainly using two different types of features: straight lines and regions to enhance the robustness of the matching algorithm; On the basis of using prior knowledge of images, combined with LSD (Line Segment Detector) line detection and template matching algorithm, by analyzing the attribute correlation between line and surface features in SAR images, selecting line and region features in SAR images to match the images, the matching accuracy between SAR images and visible light images is improved, and the probability of matching errors is reduced. The experimental results have verified that this algorithm can obtain high-precision matching results, achieve precise target positioning, and has good robustness to changes in perspective and lighting. The results are accurate and false positives are controllable.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 13 Aug 2021.
Builds on
0 of 0 references.
No references here yet.
Built on by
Citing papers per year: 2021: 1.
1 paper.
- 2021Image-free multi-character recognitioncited by 1
- 2021Image-free multi-character recognition20 Dec 2021