Using Sparse Parts in Fused Information to Enhance Performance in Latent Low-Rank Representation-Based Fusion of Visible and Infrared Images

Using Sparse Parts in Fused Information to Enhance Performance in Latent Low-Rank Representation-Based Fusion of Visible and Infrared Images

Latent Low-Rank Representation (LatLRR) has emerged as a prominent approach for fusing visible and infrared images. In this approach, images are decomposed into three fundamental components: the base part, salient part, and sparse part. The aim is to blend the base and salient features to reconstruc...

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Bibliographic Details
Main Authors:	Chen-Yu Hao, Yao-Chung Chen, Fang-Shii Ning, Tien-Yin Chou, Mei-Hsin Chen
Format:	Article
Language:	English
Published:	MDPI AG 2024-02-01
Series:	Sensors
Subjects:	Latent Low-Rank Representation (LatLRR) sparse part Convolutional Neural Network (CNN) VGG19 ResNet50 image fusion
Online Access:	https://www.mdpi.com/1424-8220/24/5/1514

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