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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...
Pfanzagl and Wefelmeyer (1978) show that bias corrected ML estimators are higher order efficient. Their procedure however is computationally complicated because it requires integrating complicat...
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 ...
The tropical forest is depleting at a fast rate due to deforestation and degradation. Illegal logging was reported to be the cause of 50% of the deforestation. Illegal logging is a very pressing iss...
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...
Maximum Likelihood Method (MLM) has been one of the most traditional classification methods in remote sensing field, but its disadvantages have been also pointed out. While a prior occurrence probabi...
DISCRIMINATION ABILITY OF NEURAL NETWORK AND MAXIMUM LIKELIHOOD CLASSIFIERS.
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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