A New Statistical Similarity Measure for Change Detection in Multitemporal SAR Images and Its Extension to Multiscale Change Analysis

By Jordi Inglada, Grégoire Mercier. IEEE Transactions on Geoscience and Remote Sensing, 2007

547 citations recorded by the source corpus.

How researchers see this paper

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Multimodal Classification of Remote Sensing Images: A Review and Future Directions (2015, methodology): “To this end, techniques such as change vector analysis, image differencing and ratioing [146], information-theoretic distances [152], likelihood ratios [153], or copula functions [154] can be applied.”
Change Detection in Synthetic Aperture Radar Images based on Image Fusion and Fuzzy Clustering (2012, methodology): “With the help of this technique we will find out difference between images, and the result shows that RFLICM is better than any other old systems.”
Kernel-Based Framework for Multitemporal and Multisource Remote Sensing Data Classification and Change Detection (2008, background): “divergence has been proposed with good results [24].”
Comparison of approximation methods to Kullback–Leibler divergence between Gaussian mixture models for satellite image retrieval (2016, methodology): “It was applied to change detection in (Inglada and Mercier 2007) by analyzing the the evolution of the local statistics of the image between two dates.”
Change Detection in Synthetic Aperture Radar Images Based on Deep Neural Networks (2016, methodology): “In addition, considering the influence of speckle noise, the log ratio is widely used [7], [8].”