In this paper, we address both the classification and the detection of changes in multitemporal and multisensor remote-sensing images. We propose a technique that is based on the compound classification rule for minimum error. The basic idea of such a technique was presented in [1], where it was applied to the detection of changes in images acquired by a single optical sensor. The purpose of this paper is to present an improved version of our technique and to highlight its potentialities for the analysis of multisensor images by reporting on experiments with a real data set.
Fusion of multisensor and multitemporal data in remote-sensing image analysis
Bruzzone, Lorenzo;
1998-01-01
Abstract
In this paper, we address both the classification and the detection of changes in multitemporal and multisensor remote-sensing images. We propose a technique that is based on the compound classification rule for minimum error. The basic idea of such a technique was presented in [1], where it was applied to the detection of changes in images acquired by a single optical sensor. The purpose of this paper is to present an improved version of our technique and to highlight its potentialities for the analysis of multisensor images by reporting on experiments with a real data set.File in questo prodotto:
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