An RGB-NIR Image Fusion Method for Improving Feature Matching

International Journal of Engineering and Technology Innovation

View Publication Info
 
 
Field Value
 
Title An RGB-NIR Image Fusion Method for Improving Feature Matching
 
Creator Park, Hanhoon
 
Subject image fusion
feature matching
near-infrared (NIR)
detail boosting
 
Description The quality of RGB images can be degraded by poor weather or lighting conditions. Thus, to make computer vision techniques work correctly, images need to be enhanced first. This paper proposes an RGB image enhancement method for improving feature matching which is a core step in most computer vision techniques. The proposed method decomposes near-infrared (NIR) image into fine detail, medium detail, and base images by using weighted least squares filters (WLSF) and boosts the medium detail image. Then, the fine and boosted medium detail images are combined, and the combined NIR detail image replaces the luminance detail image of an RGB image. Experiments demonstrates that the proposed method can effectively enhance RGB image; hence more stable image features are extracted. In addition, the method can minimize the loss of the useful visual (or optical) information of the original RGB image that can be used for other vision tasks.
 
Publisher Taiwan Association of Engineering and Technology Innovation
 
Date 2020-07-01
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier http://ojs.imeti.org/index.php/IJETI/article/view/ijeti.2020.5177
10.46604/ijeti.2020.5177
 
Source International Journal of Engineering and Technology Innovation; Vol 10 No 3 (2020); 225-234
2226-809X
2223-5329
 
Language eng
 
Relation http://ojs.imeti.org/index.php/IJETI/article/view/ijeti.2020.5177/969
http://ojs.imeti.org/index.php/IJETI/article/view/ijeti.2020.5177/980
 
Rights Copyright (c) 2020 Hanhoon Park
http://creativecommons.org/licenses/by-nc/4.0
 

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