A spatial inter-view auto-regressive super-resolution scheme for multi-view image via scene matching algorithm

2013 ◽  
Author(s):  
Min Gao ◽  
Siwei Ma ◽  
Debin Zhao ◽  
Wen Gao
Keyword(s):  
Super Resolution ◽  
Matching Algorithm ◽  
Scene Matching ◽  
Resolution Scheme ◽  
Auto Regressive

Fine-Grained Urban Flow Prediction via a Spatio-Temporal Super-Resolution Scheme

2020 ◽  
pp. 360-375
Author(s):  
Rujia Shen ◽  
Jian Xu ◽  
Qing Bao ◽  
Wei Li ◽  
Hao Yuan ◽  
...  
Keyword(s):  
Super Resolution ◽  
Fine Grained ◽  
Flow Prediction ◽  
Resolution Scheme ◽  
Spatio Temporal ◽  
Urban Flow

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

Sparse Coding Super-Resolution Scheme for Chest Computed Tomography

2018 ◽  
Vol 8 (5) ◽  
pp. 1043-1050 ◽  
Author(s):  
Junko Ota ◽  
Kensuke Umehara ◽  
Naoki Ishimaru ◽  
Shunsuke Ohno ◽  
Kentaro Okamoto ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Sparse Coding ◽  
Super Resolution ◽  
Chest Computed Tomography ◽  
Resolution Scheme
Sign in / Sign up

Export Citation Format

Share Document