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24 October 2007 An adaptive parcel-based technique robust to registration noise for change detection in multitemporal VHR images
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Abstract
This paper presents a parcel-based multiscale technique robust to registration noise for unsupervised change detection in multitemporal very high geometrical resolution images. The proposed technique is based on the analysis of the statistical behavior of registration noise present in multitemporal images at different scales. In particular, the method exploits a differential analysis of the direction distributions of spectral change vectors (SCVs) computed at different resolution levels in the polar domain. The multiscale analysis permits to separate sectors associated with true changes from sectors associated with residual registration noise. In order to improve the change-detection accuracy, the presented approach exploits the spatial-contextual information contained in the neighborhood of each pixel by defining multitemporal "parcels" (i.e. small homogeneous regions shared by both original images). Change detection is achieved by applying a specific comparison algorithm to each pixel of the images at full resolution, by considering both the information on registration noise obtained from the differential analysis and the spatial-contextual information contained in the parcels. In particular, the computed change-detection map shows a high geometrical fidelity in detail representation and a sharp reduction in false alarms due to the residual registration noise. Experimental results confirm the effectiveness of the proposed approach.
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Francesca Bovolo, Lorenzo Bruzzone, and Silvia Marchesi "An adaptive parcel-based technique robust to registration noise for change detection in multitemporal VHR images", Proc. SPIE 6748, Image and Signal Processing for Remote Sensing XIII, 674806 (24 October 2007); https://doi.org/10.1117/12.739223
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