Geo-registration of Landsat data by robust matching of wavelet features

TitleGeo-registration of Landsat data by robust matching of wavelet features
Publication TypeConference Papers
Year of Publication2000
AuthorsLe Moigne J, Netanyahu NS, Masek JG, Mount D, Goward S, Honzak M
Conference NameGeoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International
Date Published2000///
Keywordsatmospheric techniques, automated mass processing/analysis system, chip-window pair, cloud shadows, Clouds, Feature extraction, feature matching, geo-registration, geometrically corrected scene, geophysical signal processing, Image matching, image registration, landmark chips, Landsat chips, Landsat data, Landsat-5 data, Landsat-7 data, overcomplete wavelet representation, pre-processed scenes, radiometrically corrected scene, REALM, Remote sensing, robust matching, robust wavelet feature matching, scenes, statistically robust techniques, sub-pixel accuracy registration, wavelet features, Wavelet transforms, window
Abstract

The goal of our project is to build an operational system, which will provide a sub-pixel accuracy registration of Landsat-5 and Landsat-7 data. Integrated within an automated mass processing/analysis system for Landsat data (REALM), the input to our registration method consists of scenes that have been geometrically and radiometrically corrected, as well as pre-processed for the detection of clouds and cloud shadows. Such pre-processed scenes are then geo-registered relative to a database of Landsat chips. This paper describes our registration process, including the use of a database of landmark chips, a feature extraction performed by an overcomplete wavelet representation, and feature matching using statistically robust techniques. Knowing the approximate longitudes and latitudes of the four corners of the scene, a subset of chips which represent landmarks included in the scene are extracted from the database. For each of these selected landmark chips, a corresponding window is extracted from the scene, and each chip-window pair is registered using our robust wavelet feature matching. First results and future directions are presented in the paper

DOI10.1109/IGARSS.2000.857287