Search results for "Multispectral"
showing 10 items of 242 documents
Compressive single-pixel multispectral Stokes polarimeter
2014
We present a single-pixel system that performs polarimetric multispectral imaging with the aid of compressive sensing techniques. We experimentally obtain the full Stokes spatial distribution of a scene for different spectral channels.
Shape from polarization: a method for solving zenithal angle ambiguity
2012
International audience; We report a multispectral based method that permits the evolution of shape from polarization setup applied to 3D shape estimation of transparent objects. The setup is based on a polarization imaging technique which is a recent imaging method based on the analysis of the polarization state of the light in the observed scene. The technique has rapidly evolved with the development of electro-optic components and some polarization cameras are now available on the market. Shape from polarization consists in measuring the azimuthal and zenithal angles characterizing the normal of each point of the observed surface. We focus on the ambiguity in the measurement of the zenith…
A support vector domain method for change detection in multitemporal images
2010
This paper formulates the problem of distinguishing changed from unchanged pixels in multitemporal remote sensing images as a minimum enclosing ball (MEB) problem with changed pixels as target class. The definition of the sphere-shaped decision boundary with minimal volume that embraces changed pixels is approached in the context of the support vector formalism adopting a support vector domain description (SVDD) one-class classifier. SVDD maps the data into a high dimensional feature space where the spherical support of the high dimensional distribution of changed pixels is computed. Unlike the standard SVDD, the proposed formulation of the SVDD uses both target and outlier samples for defi…
Cluster kernels for semisupervised classification of VHR urban images
2009
In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and wor…
Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review
2022
Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to provide an overview of the main spectral technologies and retrieval approaches for detecting crop stress in agriculture. Firstly, we present integrated views on: i) biotic and abiotic stress factors, the phases of stress, and respective plant responses, and ii) the affected traits, appropriate spectral domains and corresponding methods for measuring traits remotely. Secondly, representative result…
Impact of Spectral Resolution on Quantifying Cyanobacteria in Lakes and Reservoirs: A Machine-Learning Assessment
2022
Cyanobacterial harmful algal blooms are an increasing threat to coastal and inland waters. These blooms can be detected using optical radiometers due to the presence of phycocyanin (PC) pigments. The spectral resolution of best-available multispectral sensors limits their ability to diagnostically detect PC in the presence of other photosynthetic pigments. To assess the role of spectral resolution in the determination of PC, a large (N = 905) database of colocated in situ radiometric spectra and PC are employed. We first examine the performance of selected widely used machine-learning (ML) models against that of benchmark algorithms for hyperspectral remote sensing reflectance ( $R_{{rs}})$…
Emissitivity spectra obtained from field and laboratory measurements using the temperature and emissivity separation algorithm.
2006
Surface emissivities play an important role in thermal remote sensing, since knowledge of them is required to estimate land surface temperature with enough accuracy. They are also important in other environmental or geological studies. We show the results obtained for the emissivity spectra of different natural surfaces (water, green, and senescent vegetation) by applying the temperature and emissivity separation (TES) algorithm to ground-based measurements collected at the field with a multiband thermal radiometer. The results have been tested with data included in spectral libraries, and rms errors lower than 0.01 have been found, except for senescent vegetation. Two methods are also prop…
Use of machine learning approaches to improve non-invasive skin melanoma diagnostic method in spectral range 450 - 950nm
2020
Non-invasive skin cancer diagnostic methods develop rapidly thanks to Deep Learning and Convolutional Neural Networks (CNN). Currently, two types of diagnostics are popular: (a) using single image taken under white illumination and (b) using multiple images taken in narrow spectral bands. The first method is easier to implement, but it is limited in accuracy. The second method is more sensitive, because it is possible to use illumination considering the absorption bands of the skin chromophores and the optical properties of the skin. Currently CNN use a single white light image, due to the availability of large datasets with lesion images. Since CNN processing and analysis requires a large …
Multispectral, Fluorescent and Photoplethysmographic Imaging for Remote Skin Assessment
2017
Optical tissue imaging has several advantages over the routine clinical imaging methods, including non-invasiveness (does not change the structure of tissues), remote operation (avoids infection) and ability to quantify the tissue condition by means of specific image parameters. Dermatologists and other skin experts need compact (preferably pocket-size), self-sustained and easy-to-use imaging devices. The operational principles and designs of ten portable in-vivo skin imaging prototypes developed at the Biophotonics Laboratory of Institute of Atomic Physics and Spectroscopy, University of Latvia during the recent five years are presented in this paper. Four groups of imaging devices are con…
Determination of sea surface temperature using combined TOVS and AVHRR data. Application to the Canary Islands area, Spain
1996
Abstract The determination of sea surface temperature from satellite is performed by means of multi-channel algorithms with channels 4 and 5 of AVHRRNOAA or using radiative transfer models and radiosounding profiles of air temperature and humidity. In this work, an alternative to the current algorithms has been established. A new method combining the information supplied by sensors of TOVS and AVHRR systems onboard NOAA satellites is proposed. It is based on the split-window technique, the coefficients A and B being determined as a function of the water vapour content, which is calculated using the TOVS sensors. The T4 and T5 temperatures are supplied by the AVHRR system. Then, combining bo…