Topographic Maps and Local Contrast Changes in Natural Images
International Journal of Computer Vision
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
What Energy Functions Can Be Minimizedvia Graph Cuts?
IEEE Transactions on Pattern Analysis and Machine Intelligence
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
An Introduction to Copulas (Springer Series in Statistics)
An Introduction to Copulas (Springer Series in Statistics)
Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability)
Fast computation of a contrast-invariant image representation
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Image change detection algorithms: a systematic survey
IEEE Transactions on Image Processing
Hi-index | 0.00 |
This paper addresses the problem of change detection in multispectral satellite images. We introduce a new information theoretic-based metric between the images associated with a Markov Random Field spatial regularization. The proposed metric is parametrized through copulas and implemented over component trees representation of the images. Such topographic map based metric associated to an Ising model exhibits interesting results for both abrupt and slow changes while being robust to global illumination and contrast changes. Experiments are conducted on SPOT images of the amazonian basin for landcover monitoring.