Search results for "Spectral imaging"

Statistical atmospheric parameter retrieval largely benefits from spatial-spectral image compression

2021

The infrared atmospheric sounding interferometer (IASI) is flying on board of the Metop satellite series, which is part of the EUMETSAT Polar System. Products obtained from IASI data represent a significant improvement in the accuracy and quality of the measurements used for meteorological models. Notably, the IASI collects rich spectral information to derive temperature and moisture profiles, among other relevant trace gases, essential for atmospheric forecasts and for the understanding of weather. Here, we investigate the impact of near-lossless and lossy compression on IASI L1C data when statistical retrieval algorithms are later applied. We search for those compression ratios that yield…

Spectrodirectional Minnaert-kretrieval using CHRIS-PROBA data

2010

We report on a detailed analysis of hyperspectral and multidirectional remote sensing data acquired using the Compact High Resolution Imaging Spectrometer (CHRIS) mounted onboard the Project for On-Board Autonomy (PROBA) spacecraft. This instrument is capable of sampling reflected radiation over the visible and near-infrared (NIR) region of the solar spectrum at a spatial resolution (approx. 17 m) intermediary between sensors traditionally used in land applications (such as Landsat and Satellite Pour l’Observation de la Terre (SPOT), 30 m–50 m) and the latest instruments delivering a nominal resolution of 1 m or less. The spectral anisotropic signature of an Alpine coniferous forest during …

The Modular X- and Gamma-Ray Sensor (MXGS)of the ASIM Payload on the International Space Station

2019

The Modular X- and Gamma-ray Sensor (MXGS) is an imaging and spectral X- and Gamma-ray instrument mounted on the starboard side of the Columbus module on the International Space Station. Together with the Modular Multi-Spectral Imaging Assembly (MMIA) (Chanrion et al. this issue) MXGS constitutes the instruments of the Atmosphere-Space Interactions Monitor (ASIM) (Neubert et al. this issue). The main objectives of MXGS are to image and measure the spectrum of X- and γ-rays from lightning discharges, known as Terrestrial Gamma-ray Flashes (TGFs), and for MMIA to image and perform high speed photometry of Transient Luminous Events (TLEs) and lightning discharges. With these two instruments sp…

Design, Development and Evaluation of a System for the Detection of Aerial Parts and Measurement of Growth Indices of Bell Pepper Plant Based on Ster…

2022

During the growth of plants, monitoring them brings much benefits to the producers. This monitoring includes the measurement of physical properties, counting plants leaves, detection of plants and separation of them from weeds. All these can be done different techniques, however, the techniques are favorable that are non-destructive because plant is a very sensitive creature that any manipulation can put disorder in its growth or lead to losing leaves or branches. Imaging techniques are of the best solutions for plants growth monitoring and geometric measurements. In this regard, in this project the use of stereo imaging and multispectral data was studied. Active and passive stereo imaging …

Application of deep convolutional neural networks for the detection of anthracnose in olives using VIS/NIR hyperspectral images

2021

Anthracnose is one of the primary diseases that affect olive production before and after harvest, causing severe damage and economic losses. The objective of this work is to detect this disease in the early stages, using hyperspectral images and advanced modelling techniques of Deep Learning (DL) and convolutional neural networks (CNN). The olives were artificially inoculated with the fungus. Hyperspectral images (450–1050 nm) of each olive were acquired until visual symptoms of the disease were observed, in some cases up to 9 days. The olives were classified into two classes: control, inoculated with water, and fungi composed of olives inoculated with the fungus. The ResNet101 architecture…

Application of deep convolutional neural networks for the detection of anthracnose in olives using VIS/NIR hyperspectral images

2021

Abstract Anthracnose is one of the primary diseases that affect olive production before and after harvest, causing severe damage and economic losses. The objective of this work is to detect this disease in the early stages, using hyperspectral images and advanced modelling techniques of Deep Learning (DL) and convolutional neural networks (CNN). The olives were artificially inoculated with the fungus. Hyperspectral images (450–1050 nm) of each olive were acquired until visual symptoms of the disease were observed, in some cases up to 9 days. The olives were classified into two classes: control, inoculated with water, and fungi composed of olives inoculated with the fungus. The ResNet101 arc…

Land surface temperature derived from airborne hyperspectral scanner thermal infrared data

2006

Abstract The AHS (airborne hyperspectral scanner) instrument has 80 spectral bands covering the visible and near infrared (VNIR), short wave infrared (SWIR), mid-infrared (MIR), and thermal infrared (TIR) spectral range. The instrument is operated by Instituto Nacional de Tecnica Aerospacial (INTA) and it has been involved in several field campaigns since 2004. The main goal of this paper is to analyze the feasibility of retrieving land surface temperature from the 10 AHS thermal infrared bands, from 71 to 80, located in the region between 8 and 13 μm. For this purpose, three different methods have been considered: (i) the single-channel method, which uses only one thermal band; (ii) the sp…

Hyperspectral Imaging for Non-invasive Diagnostics of Melanocytic Lesions

2022

Malignant melanoma poses a clinical diagnostic problem, since a large number of benign lesions are excised to find a single melanoma. This study assessed the accuracy of a novel non-invasive diagnostic technology, hyperspectral imaging, for melanoma detection. Lesions were imaged prior to excision and histopathological analysis. A deep neural network algorithm was trained twice to distinguish between histopathologically verified malignant and benign melanocytic lesions and to classify the separate subgroups. Furthermore, 2 different approaches were used: a majority vote classification and a pixel-wise classification. The study included 325 lesions from 285 patients. Of these, 74 were invasi…

2021

Aging and diabetes lead to protein glycation and cause dysfunction of collagen-containing tissues. The accompanying structural and functional changes of collagen significantly contribute to the development of various pathological malformations affecting the skin, blood vessels, and nerves, causing a number of complications, increasing disability risks and threat to life. In fact, no methods of non-invasive assessment of glycation and associated metabolic processes in biotissues or prediction of possible skin complications, e.g., ulcers, currently exist for endocrinologists and clinical diagnosis. In this publication, utilizing emerging photonics-based technology, innovative solutions in mac…

Surface Emissivity Retrieval From Airborne Hyperspectral Scanner Data: Insights on Atmospheric Correction and Noise Removal

2012

Airborne multispectral imagers have been used in validation campaigns in order to acquire very high spatial resolution data as a benchmark for current or future satellite data. Imagery acquired with such sensors implies specific data processing in relation to view-angle-dependent atmospheric correction and removal or minimization of stripping-based noise. It is necessary to appropriately perform this processing in order to benefit from reference imageries of surface temperature (T) and emissivity (e) maps retrieved from thermal infrared data. In particular, e images generated from T/e separation algorithms show undesirable noise that jeopardizes their photointerpretation. This letter addres…