Distortion Robust Relative Radiometric Normalization of Multitemporal and Multisensor Remote Sensing Images Using Image Features

verfasst von

Armin Moghimi, Amin Sarmadian, Ali Mohammadzadeh, Turgay Celik, Meisam Amani, Huseyin Kusetogullari

Abstract

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.

Externe Organisation(en)

K.N. Toosi University of Technology
University of the Witwatersrand
Southwest Jiaotong University
Wood Environment & Infrastructure Solutions
Blekinge Tekniska Högskola (BTH)

Typ

Artikel

Journal

IEEE Transactions on Geoscience and Remote Sensing

Band

60

ISSN

0196-2892

Publikationsdatum

12.03.2022

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Elektrotechnik und Elektronik, Erdkunde und Planetologie (insg.)

Ziele für nachhaltige Entwicklung

SDG 15 – Lebensraum Land

Elektronische Version(en)

https://doi.org/10.1109/tgrs.2021.3063151 (Zugang: Geschlossen)