Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 44-70 |
| Seitenumfang | 27 |
| Fachzeitschrift | International Journal of Image and Data Fusion |
| Jahrgang | 13 |
| Ausgabenummer | 1 |
| Publikationsstatus | Veröffentlicht - 2022 |
| Extern publiziert | Ja |
Abstract
This paper focuses on spatial quality assessment of pan-sharpened imagery that contains valuable information of input images. Its aim is to show that fusion functions respond differently to different types of landscapes. It compares a quality assessment of an object-level procedure with that of a conventional pixel-level-based procedure which assigns uniform quality scores to all image pixels of pan-sharpened images. To do so, after performing a series of pan-sharpening evaluations, a weighted procedure for spatial quality assessments of pan-sharpening products, allocating spatially varying weight factors to the image pixels proportional to their level of spatial information content is proposed. All experiments are performed using five high-resolution image datasets using fusion products produced by three common pan-sharpening algorithms. The datasets are acquired from WorldView-2, QuickBird, and IKONOS. Experimental results show that the spatial distortion of fused images for the class vegetation cover exceeds that of man-made structures, reaching more than 4% in some cases. Our procedure can preclude illogical fidelity estimations occurring when pan-sharpened images contain different land covers. Since particular image structures are of high importance in remote sensing applications, our procedure provides a purpose-oriented estimation of the spatial quality for pan-sharpened images in comparison with conventional procedures.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Angewandte Informatik
- Erdkunde und Planetologie (insg.)
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in: International Journal of Image and Data Fusion, Jahrgang 13, Nr. 1, 2022, S. 44-70.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Varying weighted spatial quality assessment for high resolution satellite image pan-sharpening
AU - Mehravar, Soroosh
AU - Dadrass Javan, Farzaneh
AU - Samadzadegan, Farhad
AU - Toosi, Ahmad
AU - Moghimi, Armin
AU - Khatami, Reza
AU - Stein, Alfred
N1 - Funding Information: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Publisher Copyright: © 2021 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2022
Y1 - 2022
N2 - This paper focuses on spatial quality assessment of pan-sharpened imagery that contains valuable information of input images. Its aim is to show that fusion functions respond differently to different types of landscapes. It compares a quality assessment of an object-level procedure with that of a conventional pixel-level-based procedure which assigns uniform quality scores to all image pixels of pan-sharpened images. To do so, after performing a series of pan-sharpening evaluations, a weighted procedure for spatial quality assessments of pan-sharpening products, allocating spatially varying weight factors to the image pixels proportional to their level of spatial information content is proposed. All experiments are performed using five high-resolution image datasets using fusion products produced by three common pan-sharpening algorithms. The datasets are acquired from WorldView-2, QuickBird, and IKONOS. Experimental results show that the spatial distortion of fused images for the class vegetation cover exceeds that of man-made structures, reaching more than 4% in some cases. Our procedure can preclude illogical fidelity estimations occurring when pan-sharpened images contain different land covers. Since particular image structures are of high importance in remote sensing applications, our procedure provides a purpose-oriented estimation of the spatial quality for pan-sharpened images in comparison with conventional procedures.
AB - This paper focuses on spatial quality assessment of pan-sharpened imagery that contains valuable information of input images. Its aim is to show that fusion functions respond differently to different types of landscapes. It compares a quality assessment of an object-level procedure with that of a conventional pixel-level-based procedure which assigns uniform quality scores to all image pixels of pan-sharpened images. To do so, after performing a series of pan-sharpening evaluations, a weighted procedure for spatial quality assessments of pan-sharpening products, allocating spatially varying weight factors to the image pixels proportional to their level of spatial information content is proposed. All experiments are performed using five high-resolution image datasets using fusion products produced by three common pan-sharpening algorithms. The datasets are acquired from WorldView-2, QuickBird, and IKONOS. Experimental results show that the spatial distortion of fused images for the class vegetation cover exceeds that of man-made structures, reaching more than 4% in some cases. Our procedure can preclude illogical fidelity estimations occurring when pan-sharpened images contain different land covers. Since particular image structures are of high importance in remote sensing applications, our procedure provides a purpose-oriented estimation of the spatial quality for pan-sharpened images in comparison with conventional procedures.
KW - impact of landscape
KW - object-level evaluation
KW - pan-sharpened satellite imagery
KW - Spatial quality
KW - weighted average
UR - http://www.scopus.com/inward/record.url?scp=85105306264&partnerID=8YFLogxK
U2 - 10.1080/19479832.2021.1921059
DO - 10.1080/19479832.2021.1921059
M3 - Article
AN - SCOPUS:85105306264
VL - 13
SP - 44
EP - 70
JO - International Journal of Image and Data Fusion
JF - International Journal of Image and Data Fusion
SN - 1947-9832
IS - 1
ER -