Crop Classification in Satellite Images through Probabilistic Segmentation Based on Multiple Sources

Crop Classification in Satellite Images through Probabilistic Segmentation Based on Multiple Sources †

Classification methods based on Gaussian Markov Measure Field Models and other probabilistic approaches have to face the problem of construction of the likelihood. Typically, in these methods, the likelihood is computed from 1D or 3D histograms. However, when the number of information sources grows, as in the case of satellite images, the histogram construction becomes more difficult due to the...

Multi Resolution Fuzzy Segmentation of Satellite Images

Neural Network-Based Learning Kernel for Automatic Segmentation of Multiple Sclerosis Lesions on Magnetic Resonance Images

Background: Multiple Sclerosis (MS) is a degenerative disease of central nervous system. MS patients have some dead tissues in their brains called MS lesions. MRI is an imaging technique sensitive to soft tissues such as brain that shows MS lesions as hyper-intense or hypo-intense signals. Since manual segmentation of these lesions is a laborious and time consuming task, automatic segmentation ...

Experimental Study on Graph-based Image Segmentation Methods in the Classification of Satellite Images

Object recognition is one of the primary tasks in remote sensing. For example, identifying land cover based on satellite images has an important role in agriculture, environmental protection and economics. Image segmentation is an optional elementary step of the classification process. It can improve both accuracy and performance. Graph theory is a powerful tool to describe image processing alg...

multi resolution fuzzy segmentation of satellite images