Comparison of simulated annealing algorithms for image restoration
Mathematics and Computers in Simulation
Quantitative evaluation of color image segmentation results
Pattern Recognition Letters
Multiresolution Color Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Markov Random Field Models for Unsupervised Segmentation of Textured Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image segmentation evaluation: A survey of unsupervised methods
Computer Vision and Image Understanding
Natural and remote sensing image segmentation using memetic computing
IEEE Computational Intelligence Magazine
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
Hi-index | 0.00 |
The high resolution multispectral imagery needs to be segmented into regions that can be easily interpreted and which correspond roughly to the "ground truth". In this paper, we segment multispectral images MSG2, provided by meteorological satellite "Meteosat Second Generation 2", by using an approach based on support vector Markov model witch takes into account both the spectral and the spatial information. A multi-variable Gaussian distribution is used in image processing and the Gibbs energy is used to describe the process of labeling. There are several forms of Gibbs energy. We test the best known of them and evaluate the different results using the Borsotti function which is known to be more appropriate with our visual perception.