Automatic Relative Radiometric Normalization of Bi-Temporal Satellite Images Using a Coarse-to-Fine Pseudo-Invariant Features Selection and Fuzzy Integral Fusion Strategies

• Published in: Remote sensing (Basel, Switzerland) Vol. 14; no. 8; p. 1777
• Main Authors: Moghimi, Armin, Mohammadzadeh, Ali, Celik, Turgay, Brisco, Brian, Amani, Meisam
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2022
• Subjects: Algorithms; Bivariate analysis; change detection; Chebyshev approximation; Clusters; Datasets; Histograms; image fusion; Invariants; Land cover; Land use; Methods; Modelling; multi-temporal satellite images; pseudo-invariant features (PIFs); Regression analysis; relative radiometric normalization (RRN); Remote sensing; Robustness (mathematics); Satellite imagery; Spectral correlation

Relative radiometric normalization (RRN) is important for pre-processing and analyzing multitemporal remote sensing (RS) images. Multitemporal RS images usually include different land use/land cover (LULC) types; therefore, considering an identical linear relationship during RRN modeling may result...