Radiometric image normalization is one of the basic pre-processing methods used in satellite time series analysis. This paper presents a new multi-image approach able to estimate the parameters of relative radiometric normalization through a multiple and simultaneous regression with a dataset of a generic number of images. The method was developed to overcome the typical drawbacks of standard one-to-one techniques, where image pairs are independently processed. The proposed solution is based on multi-image pseudo-invariant features incorporated into a unique regression solved via Least Squares. Results for both simulated and real data are presented and discussed.

Date Published: 12 August 2016
PDF: 9 pages
Proc. SPIE 9688, Fourth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2016), 968807 (12 August 2016); doi: 10.1117/12.2240705

Published in SPIE Proceedings Vol. 9688:
Fourth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2016)
Kyriacos Themistocleous; Diofantos G. Hadjimitsis; Silas Michaelides; Giorgos Papadavid, Editor(s)