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In the paper, we propose a newly registration method for multi-temporal image registration. Multi-temporal image registration has two difficulties: one is how to design matching strategy to gain enoug...
Most supervised image classification methods need pure pixels for training, which complicates training when pure pixels are scarce. In these cases, it can be difficult to obtain a sufficiently large ...
Limitations and deficiencies of different remote sensing sensors in extraction of different objects caused fusion of data from different sensors to become more widespread for improving classificatio...
The phase estimation of cross-track multibaseline synthetic aperture interferometric data is usually thought to be very efficiently achieved using the maximum likelihood (ML) method. The suitability o...
This paper describes a likelihood-based segmentation and classification method for remotely sensed images. It is based on optimization of a utility function, described as a function of likelihood of a...
In this work, we propose a state-of-the-art on statistical analysis of polarimetric synthetic aperture radar (SAR) data, through the modeling of several indices. We concentrate on eight ground class...

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