An algorithm based on photo consistency for image feature point matching

2017 ◽  
Author(s):  
Wei Wu ◽  
Yunfeng Wang ◽  
Anran Wang ◽  
Yu Tang ◽  
Yifan He
Keyword(s):  
Feature Point ◽  
Image Feature ◽  
Point Matching ◽  
Feature Point Matching

Unsupervised multi-spectral image feature point matching under different lighting scenes

2021 ◽  
Author(s):  
Junchong Huang ◽  
Wei Tian ◽  
Yongkun Wen ◽  
Zhan Chen ◽  
Yuyao Huang
Keyword(s):  
Feature Point ◽  
Image Feature ◽  
Spectral Image ◽  
Point Matching ◽  
Feature Point Matching

scholarly journals Feature Point Matching Method for Aerial Image Based on Recursive Diffusion Algorithm

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 407
Author(s):  
Jiayan Shen ◽  
Xiucheng Guo ◽  
Wenzong Zhou ◽  
Yiming Zhang ◽  
Juchen Li
Keyword(s):  
Large Scale ◽  
High Density ◽  
Feature Point ◽  
Aerial Images ◽  
Image Feature ◽  
Aerial Image ◽  
Experimental Comparison ◽  
Matching Accuracy ◽  
Point Matching ◽  
Feature Point Matching

Aerial images are large-scale and susceptible to light. Traditional image feature point matching algorithms cannot achieve satisfactory matching accuracy for aerial images. This paper proposes a recursive diffusion algorithm, which is scale-invariant and can be used to extract symmetrical areas of different images. This narrows the matching range of feature points by extracting high-density areas of the image and improving the matching accuracy through correlation analysis of high-density areas. Through experimental comparison, it can be found that the recursive diffusion algorithm has more advantages compared to the correlation coefficient method and the mean shift algorithm when matching accuracy of aerial images, especially when the light of aerial images changes greatly.

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