Image Quality Assessment of UAV Hyperspectral Images Using Radiant, Spatial, and Spectral Features Based on Fuzzy Comprehensive Evaluation Method-Reference-Cited by-同舟云学术

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Image Quality Assessment of UAV Hyperspectral Images Using Radiant, Spatial, and Spectral Features Based on Fuzzy Comprehensive Evaluation Method

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Tian Wenzhong¹^ORCID,Kan Za¹^ORCID,Sanchez-Azofeifa Arturo²,Zhao Qingzhan³^ORCID,He Gaili²

Affiliation:

1. School of Mechanical and Electrical Engineering, Shihezi University, Shihezi, China

2. Centre for Earth Observation Sciences, University of Alberta, Edmonton, AB, Canada

3. School of Information Science and Technology, Shihezi University, Shihezi, China

Funder

National Natural Science Foundation of China

Major Scientific and Technological Projects of the XPCC of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/8859/10365397/10398212.pdf?arnumber=10398212

Reference15 articles.

1. Tradeoffs in the Spatial and Spectral Resolution of Airborne Hyperspectral Imaging Systems: A Crop Identification Case Study

2. A Comprehensive Performance Evaluation of Image Quality Assessment Algorithms

3. No-Reference Hyperspectral Image Quality Assessment via Quality-Sensitive Features Learning

4. Airborne hyperspectral image quality evaluation of crops based on CNN—In the case of cotton;Liu;J. Shihezi Univ. Natural Sci.,2022

5. Radiometric image quality assessment of ZY-3 TLC camera;Xu;Space Recovery Remote Sens.,2012

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1. Semantic-Aware Fusion Network Based on Super-Resolution;Sensors;2024-06-05

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