Varying weighted spatial quality assessment for high resolution satellite image pan-sharpening. (2nd January 2022)

• Record Type: Journal Article
• Authors: Mehravar, Soroosh; Dadrass Javan, Farzaneh; Samadzadegan, Farhad; Toosi, Ahmad; Moghimi, Armin; Khatami, Reza; Stein, Alfred
• Is Part Of: International journal of image and data fusion. Volume 13:Number 1(2022)
• Page Start: 44
• Page End: 70
• Publication Date: 2022-01-02
• Subjects: Spatial quality -- weighted average -- object-level evaluation -- pan-sharpened satellite imagery -- impact of landscape; Image processing -- Periodicals; Multisensor data fusion -- Periodicals; Multisensor data fusion; Periodicals; 621.36705
• DOI: 10.1080/19479832.2021.1921059
• Languages: English
• ISSNs: 1947-9832

Abstract

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.