Search results for "Hyperspectral"
showing 10 items of 271 documents
Large scale semi-supervised image segmentation with active queries
2011
A semiautomatic procedure to generate classification maps of remote sensing images is proposed. Starting from a hierarchical unsupervised classification, the algorithm exploits the few available labeled pixels to assign each cluster to the most probable class. For a given amount of labeled pixels, the algorithm returns a classified segmentation map, along with confidence levels of class membership for each pixel. Active learning methods are used to select the most informative samples to increase confidence in the class membership. Experiments on a AVIRIS hyperspectral image confirm the effectiveness of the method, especially when used with active learning query functions and spatial regular…
A Support Vector Domain Description Approach to Supervised Classification of Remote Sensing Images
2007
This paper addresses the problem of supervised classification of remote sensing images in the presence of incomplete (nonexhaustive) training sets. The problem is analyzed according to two different perspectives: 1) description and recognition of a specific land-cover class by using single-class classifiers and 2) solution of multiclass problems with single-class classification techniques. In this framework, we analyze different one-class classifiers and introduce in the remote sensing community the support vector domain description method (SVDD). The SVDD is a kernel-based method that exhibits intrinsic regularization ability and robustness versus low numbers of high-dimensional samples. T…
Sun Induced Fluorescence Calibration and Validation for Field Phenotyping
2018
Reliable measurements of Sun Induced Fluorescence (SIF) require a good instrument characterization as well as a complex processing chain. In this paper, we summarize the state of the art SIF retrieval methods and measurements platforms for field phenotyping. Furthermore, we use HyScreen, hyperspectral-imaging system for top of canopy measurements of SIF, as an example of the instrument requirements, data process, and data validation needed to obtain reliable measurements of SIF.
HICO L1 and L2 data processing: Radiometric recalibration, atmospheric correction and retrieval of water quality parameters
2015
The Hyperspectral Imager for the Coastal Ocean (HICO) is an imaging spectrometer designed with a very high signal-to-noise ratio to monitor coastal ocean and inland waters. The processing of Top-Of-Atmosphere radiance data down to surface reflectance is fundamental for the retrieval of water quality products. However, the current HICO processing chain does not provide atmospheric corrected data nor higher-level water quality products. This paper describes the algorithms implemented within an HICO data processing chain that includes image pre-processing, atmospheric correction and the retrieval of water quality parameters. The implemented algorithms have been validated over a set of HICO ima…
HICO level-2 data processing toolbox for the atmospheric correction and the retrieval of water quality parameters
2014
The Hyperspectral Imager for the Coastal Ocean (HICO) is an imaging spectrometer specifically designed to monitor the coastal ocean. The processing of Top-Of-Atmosphere (TOA) radiance data down to surface reflectance is fundamental for the retrieval of water quality products. However, the current HICO processing chain does not provide atmospheric corrected data nor higher-level water quality products. This work describes a toolbox for the atmospheric correction of HICO data and the retrieval of water quality products. The HICO toolbox, consisting on three main modules (image pre-processing, atmospheric correction and retrieval of water quality products), has been used over a set of HICO ima…
Noise reduction in asteroid imaging using a miniaturized spectral imager
2021
In October 2024, European Space Agency’s Hera mission will be launched, targeting the binary asteroid Didymos. Hera will host the Juventas and Milani CubeSats, the first CubeSats to orbit close to a small celestial body performing scientific and technological operations. The primary scientific payload of the Milani CubeSat is the SWIR, NIR, and VIS imaging spectrometer ASPECT. The Milani mission objectives include mapping the global composition and the characterization of the binary asteroid surface. Onboard data processing and evaluation steps will be applied due to the limited data budget for the downlink to Earth and to perform the technological demonstration of a novel semi-autonomous h…
Multispectral integral imaging acquisition and processing using a monochrome camera and a liquid crystal tunable filter
2012
This paper presents an acquisition system and a procedure to capture 3D scenes in different spectral bands. The acquisition system is formed by a monochrome camera, and a Liquid Crystal Tunable Filter (LCTF) that allows to acquire images at different spectral bands in the [480, 680]nm wavelength interval. The Synthetic Aperture Integral Imaging acquisition technique is used to obtain the elemental images for each wavelength. These elemental images are used to computationally obtain the reconstruction planes of the 3D scene at different depth planes. The 3D profile of the acquired scene is also obtained using a minimization of the variance of the contribution of the elemental images at each …
Using Wave Propagation Simulations and Convolutional Neural Networks to Retrieve Thin Film Thickness from Hyperspectral Images
2021
Ill-posed inversion problems are one of the major challenges when there is a need to combine measurements with the theory and numerical model. In this study, we demonstrate the use of wave propagation simulations to train a convolutional neural network (CNN) for retrieving sub-wavelength thickness profiles of thin film coatings from hyperspectral images. The simulations are produced by solving numerically one-dimensional wave equation with a method based on Discrete Exterior Calculus (DEC). This approach provides a powerful tool to produce large sets of training data for the neural network. CNN was verified by simulated verification sets and measured reflectance spectra, both of which showe…
Regression Wavelet Analysis for Lossless Coding of Remote-Sensing Data
2016
A novel wavelet-based scheme to increase coefficient independence in hyperspectral images is introduced for lossless coding. The proposed regression wavelet analysis (RWA) uses multivariate regression to exploit the relationships among wavelet-transformed components. It builds on our previous nonlinear schemes that estimate each coefficient from neighbor coefficients. Specifically, RWA performs a pyramidal estimation in the wavelet domain, thus reducing the statistical relations in the residuals and the energy of the representation compared to existing wavelet-based schemes. We propose three regression models to address the issues concerning estimation accuracy, component scalability, and c…
Discrete wavelet transform based multispectral filter array demosaicking
2013
International audience; The idea of colour filter array may be adapted to multi-spectral image acquisition by integrating more filter types into the array, and developing associated demosaicking algorithms. Several methods employing discrete wavelet transform (DWT) have been proposed for CFA demosaicking. In this work, we put forward an extended use of DWT for mul-tispectral filter array demosaicking. The extension seemed straightforward, however we observed striking results. This work contributes to better understanding of the issue by demonstrating that spectral correlation and spatial resolution of the images exerts a crucial influence on the performance of DWT based demosaicking.