A method of supervised characterisation of synthetic aperture radar (SAR) satellite imageshas been discussed in which simple object shape features of satellite images have been usedto classify and describe the terrain types. This scheme is based on a multilevel approach inwhich objects of interest are first segmented out from the image and subsequently characterisedbased on their shape features. Once all objects have been characterised, the entire image canbe characterised. Emphasis has been laid on the hierarchical information extraction from theimage which enables greater flexibility in characterising the image and is not restricted to mereclassification. The paper also describes a method for giving relative importance among features,i.e....
SAR images are the images captured through satellite or radar to monitor the specific geographical a...
The problem of selection of objects of different nature in digital monochrome images obtained by rem...
International audienceIn this paper, we develop a novel classification approach for multiresolution,...
A method of supervised characterisation of synthetic aperture radar (SAR) satellite imageshas been d...
A method of supervised characterisation of synthetic aperture radar (SAR) satellite images has been ...
In the last years, the spatial resolution of remote sensing sensors and imagery has continuously imp...
Abstract — We introduce the hierarchical Markov aspect model (HMAM), a computationally efficient gra...
Advances in spatial and spectral resolution of satellite images have led to tremendous growth in lar...
Abstract—In this letter, we propose a theoretically and compu-tationally simple feature for syntheti...
This paper presents a classification approach based on attribute learning for high spatial resolutio...
Application of ultra-wideband signals and large apertures makes it possible to obtain a sufficiently...
Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilk...
With various remote sensing technologies to aid Earth Observation, radar-based imaging is one of the...
This paper proposes a new method for the classification of synthetic aperture radar (SAR) images bas...
Image segmentation and object detection are two fundamental but major applications of machine intell...
SAR images are the images captured through satellite or radar to monitor the specific geographical a...
The problem of selection of objects of different nature in digital monochrome images obtained by rem...
International audienceIn this paper, we develop a novel classification approach for multiresolution,...
A method of supervised characterisation of synthetic aperture radar (SAR) satellite imageshas been d...
A method of supervised characterisation of synthetic aperture radar (SAR) satellite images has been ...
In the last years, the spatial resolution of remote sensing sensors and imagery has continuously imp...
Abstract — We introduce the hierarchical Markov aspect model (HMAM), a computationally efficient gra...
Advances in spatial and spectral resolution of satellite images have led to tremendous growth in lar...
Abstract—In this letter, we propose a theoretically and compu-tationally simple feature for syntheti...
This paper presents a classification approach based on attribute learning for high spatial resolutio...
Application of ultra-wideband signals and large apertures makes it possible to obtain a sufficiently...
Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilk...
With various remote sensing technologies to aid Earth Observation, radar-based imaging is one of the...
This paper proposes a new method for the classification of synthetic aperture radar (SAR) images bas...
Image segmentation and object detection are two fundamental but major applications of machine intell...
SAR images are the images captured through satellite or radar to monitor the specific geographical a...
The problem of selection of objects of different nature in digital monochrome images obtained by rem...
International audienceIn this paper, we develop a novel classification approach for multiresolution,...