The Regularized Iteratively Reweighted MAD Method for Change Detection in Multi- and Hyperspectral Data


This paper describes new extensions to the previously published multivariate alteration detection (MAD) method for change detection in bi-temporal, multi- and hypervariate data such as remote sensing imagery. Much like boosting methods often applied in data mining work, the iteratively reweighted (IR) MAD method in a series of iterations places increasing… (More)
DOI: 10.1109/TIP.2006.888195


Figures and Tables

Sorry, we couldn't extract any figures or tables for this paper.


Citations per Year

207 Citations

Semantic Scholar estimates that this publication has 207 citations based on the available data.

See our FAQ for additional information.

Slides referencing similar topics