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Change detection in large urban areas is an application with increasing relevance. In this domain, Polarimetric SAR (PolSAR) sensors are receiving more attention recently. The enhanced polarimetric information provides useful features which can describe multi-temporal changes. In this work, we aim at introducing an approach for unsupervised change detection with focus on built-up areas that relies...
A novel spectral-spatial joint multiscale approach is developed to address the multi-class change detection problem in bitemporal multispectral remote sensing images. The proposed approach is based on a multiscale morphological compressed change vector analysis (M2C2VA), which extend the state-of-the-art spectrum-based compressed change vector analysis (C2VA) while preserving more geometrical details...
In this paper, a segmentation-based approach to fine registration of multispectral and multitemporal very high resolution (VHR) images is proposed. The proposed approach aims at estimating and correcting the residual local misalignment [also referred to as registration noise (RN)] that often affects multitemporal VHR images even after standard registration. The method extracts automatically a set...
This paper develops a novel multitemporal spectral unmixing (MSU) approach for addressing the challenging multiple-change detection problem in bi-temporal hyperspectral (HS) images. Differently from state-of-the-art techniques that mainly perform at a pixel level, the proposed MSU approach investigates the spectral-temporal variations at a subpixel level. A multitemporal spectral mixture model is...
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