1,793 research outputs found
Deep learning in remote sensing: a review
Standing at the paradigm shift towards data-intensive science, machine
learning techniques are becoming increasingly important. In particular, as a
major breakthrough in the field, deep learning has proven as an extremely
powerful tool in many fields. Shall we embrace deep learning as the key to all?
Or, should we resist a 'black-box' solution? There are controversial opinions
in the remote sensing community. In this article, we analyze the challenges of
using deep learning for remote sensing data analysis, review the recent
advances, and provide resources to make deep learning in remote sensing
ridiculously simple to start with. More importantly, we advocate remote sensing
scientists to bring their expertise into deep learning, and use it as an
implicit general model to tackle unprecedented large-scale influential
challenges, such as climate change and urbanization.Comment: Accepted for publication IEEE Geoscience and Remote Sensing Magazin
Integration of Vessel-Based Hyperspectral Scanning and 3D-Photogrammetry for Mobile Mapping of Steep Coastal Cliffs in the Arctic
Remote and extreme regions such as in the Arctic remain a challenging ground for geological mapping and mineral exploration. Coastal cliffs are often the only major well-exposed outcrops, but are mostly not observable by air/spaceborne nadir remote sensing sensors. Current outcrop mapping efforts rely on the interpretation of Terrestrial Laser Scanning and oblique photogrammetry, which have inadequate spectral resolution to allow for detection of subtle lithological differences. This study aims to integrate 3D-photogrammetry with vessel-based hyperspectral imaging to complement geological outcrop models with quantitative information regarding mineral variations and thus enables the differentiation of barren rocks from potential economic ore deposits. We propose an innovative workflow based on: (1) the correction of hyperspectral images by eliminating the distortion effects originating from the periodic movements of the vessel; (2) lithological mapping based on spectral information; and (3) accurate 3D integration of spectral products with photogrammetric terrain data. The method is tested using experimental data acquired from near-vertical cliff sections in two parts of Greenland, in Karrat (Central West) and Søndre Strømfjord (South West). Root-Mean-Square Error of (6.7, 8.4) pixels for Karrat and (3.9, 4.5) pixels for Søndre Strømfjord in X and Y directions demonstrate the geometric accuracy of final 3D products and allow a precise mapping of the targets identified using the hyperspectral data contents. This study highlights the potential of using other operational mobile platforms (e.g., unmanned systems) for regional mineral mapping based on horizontal viewing geometry and multi-source and multi-scale data fusion approaches
Probe-based Rapid Hybrid Hyperspectral and Tissue Surface Imaging Aided by Fully Convolutional Networks
Tissue surface shape and reflectance spectra provide rich intra-operative
information useful in surgical guidance. We propose a hybrid system which
displays an endoscopic image with a fast joint inspection of tissue surface
shape using structured light (SL) and hyperspectral imaging (HSI). For SL a
miniature fibre probe is used to project a coloured spot pattern onto the
tissue surface. In HSI mode standard endoscopic illumination is used, with the
fibre probe collecting reflected light and encoding the spatial information
into a linear format that can be imaged onto the slit of a spectrograph.
Correspondence between the arrangement of fibres at the distal and proximal
ends of the bundle was found using spectral encoding. Then during pattern
decoding, a fully convolutional network (FCN) was used for spot detection,
followed by a matching propagation algorithm for spot identification. This
method enabled fast reconstruction (12 frames per second) using a GPU. The
hyperspectral image was combined with the white light image and the
reconstructed surface, showing the spectral information of different areas.
Validation of this system using phantom and ex vivo experiments has been
demonstrated.Comment: This paper has been submitted to MICCAI2016 on 17 March, 2016, and
conditionally accepted on 2 June, 201
The HYPSOS optomechanical bench design
In the last years, almost all the planetary missions have included a stereo camera and a spectrograph on-board. These two instruments respectively provide stereo images and spectral information, essential data to characterize a planet's surface. HYPSOS (HYPerspectral Stereo Observing System) is a novel instrument that will be able to merge the function of the two instruments. In fact, it will produce stereo hypercubes and represent 3D data with a fourth dimension: the spectral information.openEmbargo temporaneo per motivi di segretezza e/o di proprietà dei risultati e informazioni di enti esterni o aziende private che hanno partecipato alla realizzazione del lavoro di ricerca relativo alla tes
- …