A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A multiscale change detection technique robust to registration noise
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
IEEE Transactions on Image Processing
Statistical change detection with moments under time-varying illumination
IEEE Transactions on Image Processing
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IEEE Transactions on Image Processing
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IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
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IEEE Transactions on Image Processing
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IEEE Transactions on Image Processing
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Computers & Geosciences
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This paper presents an automatic context-sensitive technique robust to registration noise (RN) for change detection (CD) in multitemporal very high geometrical resolution (VHR) remote sensing images. Exploiting the properties of RN in VHR images, the proposed technique analyzes the distribution of the spectral change vectors (SCVs) computed according to the change vector analysis (CVA) in a quantized polar domain. The method studies the SCVs falling into each quantization cell at different resolution levels (scales) to automatically identify the effects of RN in the polar domain. This information is jointly exploited with the spatial context information contained in the neighborhood of each pixel for generating the final CD map. The spatial context information is modeled through the definition of adaptive regions homogeneous both in spatial and temporal domain (parcels). Experimental results obtained on real VHR remote sensing multitemporal images confirm the effectiveness of the proposed technique.