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Superpixel-based Structural Similarity Metric for Image Fusion Quality Evaluation

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成果类型:
期刊论文
作者:
Eryan Wang;Bin Yang;Lihui Pang
通讯作者:
Yang, Bin(yangbin01420@163.com)
作者机构:
[Eryan Wang; Bin Yang; Lihui Pang] College of Electric Engineering, University of South China, Hengyang
421001, China
[Eryan Wang; Bin Yang; Lihui Pang] 421001, China
通讯机构:
[Bin Yang] C
College of Electric Engineering, University of South China, Hengyang, China
语种:
英文
关键词:
Image Fusion Quality Assessment;Image Feature;Human Visual System;Superpixel Segmentation;Structural Similarity Metric;Adaptive Superpixel
期刊:
Sensing and Imaging
ISSN:
1557-2064
年:
2021
卷:
22
期:
1
页码:
1-25
基金类别:
National Natural Science Foundation of China#&#&#61871210#&#&#61901209 Scientific Research Fund of Hunan Provincial Education Department#&#&#16B225 Natural Science Foundation of Hunan Province#&#&#2016JJ3106 Chuanshan Talent Project of the University of South China construct program of key disciplines in USC#&#&#NHXK04
机构署名:
本校为第一且通讯机构
院系归属:
电气工程学院
摘要:
Image fusion refers to integrate multiple images of the same scene into a high-quality fused image. Universal quality evaluation for fused image is one of the urgent problems in the field of image fusion. Typically, local features extracted from rectangular blocks of the fused images are used to achieve objective evaluation. However, the fixed shape of image block is neither suitable for the natural attributes of an image, nor for the perceptual characteristics of human visual system. To deal with the problem, a superpixel-based structural simi...

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