Component trees for image sequences and streams

Abstract

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Classification of Remote Sensing Data With Morphological Attribute Profiles: A decade of advances

“…While the application of APs to optical remote sensing data has been strongly focused on, alternative remote sensing image types have received far less attention. One may witness some tentative works on SAR (Synthetic Aperture Radar) and polarimetric SAR images for segmentation [33], building detection [34], crop field and land-cover classification [35], [36] and change detection [37]- [39] using the original APs and the Differential Attribute Profiles; on passive microwave remote sensing image analysis [40]; on LiDAR data for building detection [41] and land cover classification [16], [28], [42]- [44]; on satellite image time-series classification using Sentinel-2 data [45], [46]; on the fusion of APs and Extinction Profiles (a variant of AP that will be discussed in Sec. III-F) of hyperspectral and LiDAR data using composite kernel SVM [47], [48] and deep learning approaches [49], [50] for land cover classification.…”

Spatio-Temporal Object Stability for Monitoring Evolving Areas in Satellite Image Time Series

“…Morphological hierarchies are multiscale representations of an image that provide access to the objects it contains at various scales-of-interest. More specifically, the question of building a morphological hierarchy for modelling a time series was addressed in our previous work (Tuna et al, 2020). We have used a component tree to observe the spatial structures in the time domain through temporal connectivity.…”

“…We recall here how to build a morphological hierarchy, that represents an image through a tree structure. Furthermore, we describe the space-time tree model recently proposed in (Tuna et al, 2020) that we use to derive our spatio-temporal stability attribute.…”

“…While morphological hierarchies have been built from still images for decades, their definition over spatio-temporal data such as satellite image time series is more recent. In (Tuna et al, 2020), several strategies to build such a hierarchy have been introduced, and we focus here on the space-time tree. It assumes the SITS being seen as a spatio-temporal cube, where the two usual spatial dimensions are completed by a third dimension related to time.…”

Editorial — Virtual Special Issue: “Hierarchical Representations: New Results and Challenges for Image Analysis”

“…Such a method is suitable for use on embedded and robotics systems. Tuna et al (2020) investigate the ways to represent and analyze image sequences with morphological hierarchies. A review of different strategies to build spatial, temporal and spatial-temporal hierarchies from an image sequence is provided.…”