Improved UAV Scene Matching Algorithm Based on CenSurE Features and FREAK Descriptor

2020 ◽  
pp. 158-167
Author(s):  
Chenglong Wang ◽  
Tangle Peng ◽  
Longzhi Hu ◽  
Guanjun Liu
Keyword(s):  
Matching Algorithm ◽  
Scene Matching

High-Speed and Robust Scene Matching Algorithm Based on ORB for SAR/INS Integrated Navigation System

2012 ◽  
Vol 241-244 ◽  
pp. 439-443
Author(s):  
Fang Chen ◽  
Yun Xi Xu
Keyword(s):  
Navigation System ◽  
High Speed ◽  
Hamming Distance ◽  
Reference Image ◽  
Integrated Navigation ◽  
Sar Images ◽  
Matching Algorithm ◽  
Integrated Navigation System ◽  
Scene Matching ◽  
Position Errors

It is important that scene matching algorithm should satisfy the requirements of real-time, robustness and high-precision for inertial integrated navigation system. And considering the serious distortion and speckle noises of SAR images, we proposed a new scene matching algorithm for the SAR/INS integrated navigation system with high-speed and robustness based on Oriented FAST and Rotated BRIEF (ORB). We started by detecting scale-space FAST-based features in combination with an efficiently computed orientation in the image. Then, we calculated feature point's Rotation-Aware BRIEF descriptor which performs well with rotation and match features by computing Hamming distance between descriptors. Finally, we adopted GroupSAC which are proposed recently to remove the false matching points and the least square algorithm for getting the distortion transformation parameters that are the aircraft position errors and rotation transform parameters between real image and reference image. Experimental results on real SAR images indicate that our algorithm is invariant to various image transformations due to rotation and scale, and also robust to speckle noise and extremely efficient to compute, better than SIFT in many situations. Therefore, our algorithm can meet the high performance needs for matching navigation in the SAR/INS integrated navigation system.

Scene matching algorithm for SAR images based on SIFT features

2009 ◽  
Vol 28 (9) ◽  
pp. 2404-2406 ◽  
Author(s):  
Zhao-hui YANG ◽  
Ying CHEN ◽  
Yong-she SHAO ◽  
Shao-ming ZHANG
Keyword(s):  
Sar Images ◽  
Matching Algorithm ◽  
Scene Matching ◽  
Sift Features

Dynamic Key-Frame Based Airborne Scene Matching Vision Navigation

2011 ◽  
Author(s):  
Yaojun Li ◽  
Quan Pan ◽  
Chunhui Zhao ◽  
Feng Yang ◽  
Yongmei Cheng
Keyword(s):  
Image Sequence ◽  
Visual Navigation ◽  
Vision Navigation ◽  
Matching Algorithm ◽  
Scene Matching ◽  
Key Frame ◽  
Dynamic Key ◽  
Inter Frame ◽  
Navigation Method ◽  
Navigation Scheme

In order to develop a backup navigation scheme for allowing temporally GPS faults or degradations, this paper proposes a dynamic key-frame-based natural-landmark scene matching visual navigation method for UAV. Firstly, this method could autonomously describe and check featured natural landmarks by analyzing image sequence from on-board camera. Secondly, After abstraction of key-frames including featured natural landmark, UAV will be located by the means of NLSM (Natural-Landmark Scene Matching) which based on dynamic key-frame. Thirdly, this navigation scheme adopt inter-frame scene matching algorithm in order to improving the navigation performance of accuracy, reliability and runtime. Experiments show that the vision navigation scheme proposed fits the requirements of navigation in complex and unknown environment for UAV.

scholarly journals Robust Performance of Scene Matching Algorithm

2013 ◽  
Vol 06 (05) ◽  
pp. 6-10
Author(s):  
Zhaohui Xia ◽  
Xiaogang Yang ◽  
Fei Meng ◽  
Shicheng Wang
Keyword(s):  
Robust Performance ◽  
Matching Algorithm ◽  
Scene Matching
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