Georegistration of Landsat data via robust matching of multiresolution features
| Autor: | J. G. Masek, Nathan S. Netanyahu, J. Le Moigne |
|---|---|
| Rok vydání: | 2004 |
| Předmět: |
Landmark
business.industry Computer science Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image registration Pattern recognition Subpixel rendering Wavelet Thematic Mapper General Earth and Planetary Sciences Computer vision Artificial intelligence Electrical and Electronic Engineering business |
| Zdroj: | IEEE Transactions on Geoscience and Remote Sensing. 42:1586-1600 |
| ISSN: | 0196-2892 |
| DOI: | 10.1109/tgrs.2004.826822 |
| Popis: | The goal of the project described in this paper is to build a prototype of an operational system, which will provide registration within subpixel accuracy of multitemporal Landsat data, acquired by either Landsat-5 or Landsat-7 Thematic Mapper instruments. Integrated within an automated mass processing system for Landsat data, the input to our registration system consists of scenes that have been geometrically and radiometrically corrected, as well as preprocessed for detection of clouds and cloud shadows. Such preprocessed scenes are then georegistered relative to a database of Landsat chips. This paper describes the entire registration process, including the use of landmark chips, feature extraction performed by an overcomplete wavelet representation, and feature matching using statistically robust techniques. Knowing the approximate longitudes and latitudes or the UTM coordinates of the four corners of each incoming scene, a subset of the chips that represent landmarks included in the scene are selected to perform the registration. For each of these selected landmark chips, a corresponding window is extracted from the incoming scene, and each chip-window pair is registered using a robust wavelet feature-matching methodology. Based on the transformations from the chip-window pairs, a global transformation is then computed for the entire scene using a variant of a robust least median of squares estimator. Empirical results of this registration process, which provided subpixel accuracy for several multitemporal scenes from different study areas, are presented and discussed. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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