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Distortion Robust Relative Radiometric Normalization of Multitemporal and Multisensor Remote Sensing Images Using Image Features
K. N. Toosi University of Technology, IRN.
K. N. Toosi University of Technology, IRN.
K. N. Toosi University of Technology, IRN.
University of the Witwatersrand, ZAF.
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2022 (English)In: IEEE Transactions on Geoscience and Remote Sensing, ISSN 0196-2892, E-ISSN 1558-0644, Vol. 60, article id 5400820Article in journal (Refereed) Published
Abstract [en]

In this article, we propose a novel framework to radiometrically correct unregistered multisensor image pairs based on the extracted feature points with the KAZE detector and the conditional probability (CP) process in the linear model fitting. In this method, the scale, rotation, and illumination invariant radiometric control set samples (SRII-RCSS) are first extracted by the blockwise KAZE strategy. They are then distributed uniformly over both textured and texture-less land use/land cover (LULC) using grid interpolation and a set of nearest-neighbors. Subsequently, SRII-RCSS are scored by a similarity measure, and the histogram of the scores is then used to refine SRII-RCSS. The normalized subject image is produced by adjusting the subject image to the reference image using the CP-based linear regression (CPLR) based on the optimal SRII-RCSS. The registered normalized image is finally generated by registration of the normalized subject image to the reference image through a two-pass registration method, namely affine-B-spline and, then, it is enhanced by updating the normalization coefficient of CPLR based on the SRII-RCSS. In this study, eight multitemporal data sets acquired by inter/intra satellite sensors were used in tests to comprehensively assess the efficiency of the proposed method. Experimental results show that the proposed method outperforms the existing state-of-the-art relative radiometric normalization (RRN) methods both qualitatively and quantitatively, indicating its capability for RRN of unregistered multisensor image pairs. IEEE

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2022. Vol. 60, article id 5400820
Keywords [en]
Change detection, feature detection, Feature extraction, feature matching, image matching, Image sensors, Linear regression, Radiometry, relative radiometric normalization, Remote sensing, rotation invariant, Satellite broadcasting, scale invariant., Sensors, Interpolation, Land use, Textures, Conditional probabilities, Illumination invariant, Land use/land cover, Multi sensor images, Multi-temporal data, Multisensor remote sensing, Registration methods, Image enhancement
National Category
Computer Vision and Robotics (Autonomous Systems) Remote Sensing
Identifiers
URN: urn:nbn:se:bth-21295DOI: 10.1109/TGRS.2021.3063151ISI: 000728266600088Scopus ID: 2-s2.0-85102687149OAI: oai:DiVA.org:bth-21295DiVA, id: diva2:1540123
Available from: 2021-03-26 Created: 2021-03-26 Last updated: 2022-01-03Bibliographically approved

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Kusetogullari, Hüseyin

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