Object-based change detection and classification

Irmgard Niemeyer; Florian Bachmann; André John; Clemens Listner; Prashanth Reddy Marpu

doi:10.1117/12.830409

28 September 2009 Object-based change detection and classification

Irmgard Niemeyer, Florian Bachmann, André John, Clemens Listner, Prashanth Reddy Marpu

Proceedings Volume 7477, Image and Signal Processing for Remote Sensing XV; 74770S (2009) https://doi.org/10.1117/12.830409
Event: SPIE Remote Sensing, 2009, Berlin, Germany

Abstract

The paper presents some recent developments on object-based change detection and classification. In detail, the following algorithms were implemented either as Matlab or IDL programmes or as plug-ins for Definiens Developer: i) object-based change detection: segmentation of bitemporal datasets, change detection using the Multivariate Alteration Detection1 based on object features; ii) object features and object feature extraction: moment invariants, automated extraction of object features using Bayesian statistics; iii) object-based classification by neural networks: FFN and Class- dependent FFN using five different learning algorithms. The paper introduces the methodologies, describes the implementation and gives some examples results on the application.

Citation Download Citation

Irmgard Niemeyer, Florian Bachmann, André John, Clemens Listner, and Prashanth Reddy Marpu "Object-based change detection and classification", Proc. SPIE 7477, Image and Signal Processing for Remote Sensing XV, 74770S (28 September 2009); https://doi.org/10.1117/12.830409

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