scholarly journals GEOMETRIC CALIBRATION AND RADIOMETRIC CORRECTION OF THE MAIA MULTISPECTRAL CAMERA

2017 ◽  
Vol XLII-3/W3 ◽  
pp. 149-156 ◽  
Author(s):  
E. Nocerino ◽  
M. Dubbini ◽  
F. Menna ◽  
F. Remondino ◽  
M. Gattelli ◽  
...  
Keyword(s):  
Near Infrared ◽  
Multispectral Imaging ◽  
Low Cost ◽  
Electromagnetic Spectrum ◽  
Radiometric Correction ◽  
Geometric Calibration ◽  
Remote Sensing Technique ◽  
Band Pass ◽  
Imaging Sensors ◽  
Multispectral Camera

Multispectral imaging is a widely used remote sensing technique, whose applications range from agriculture to environmental monitoring, from food quality check to cultural heritage diagnostic. A variety of multispectral imaging sensors are available on the market, many of them designed to be mounted on different platform, especially small drones. This work focuses on the geometric and radiometric characterization of a brand-new, lightweight, low-cost multispectral camera, called MAIA. The MAIA camera is equipped with nine sensors, allowing for the acquisition of images in the visible and near infrared parts of the electromagnetic spectrum. Two versions are available, characterised by different set of band-pass filters, inspired by the sensors mounted on the WorlView-2 and Sentinel2 satellites, respectively. The camera details and the developed procedures for the geometric calibrations and radiometric correction are presented in the paper.

scholarly journals Enhancing Image-Based Multiscale Heritage Recording with Near-Infrared Data

2020 ◽  
Vol 9 (4) ◽  
pp. 269 ◽  
Author(s):  
Efstathios Adamopoulos ◽  
Fulvio Rinaudo
Keyword(s):  
Near Infrared ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
Archaeological Site ◽  
Short Review ◽  
Additional Information ◽  
3D Point Clouds ◽  
Heritage Science ◽  
Imaging Sensors

Passive sensors, operating in the visible (VIS) spectrum, have widely been used towards the trans-disciplinary documentation, understanding, and protection of tangible cultural heritage (CH). Although, many heritage science fields benefit significantly from additional information that can be acquired in the near-infrared (NIR) spectrum. NIR imagery, captured for heritage applications, has been mostly investigated with two-dimensional (2D) approaches or by 2D-to-three-dimensional (3D) integrations following complicated techniques, including expensive imaging sensors and setups. The availability of high-resolution digital modified cameras and software implementations of Structure-from-Motion (SfM) and Multiple-View-Stereo (MVS) algorithms, has made the production of models with spectral textures more feasible than ever. In this research, a short review of image-based 3D modeling with NIR data is attempted. The authors aim to investigate the use of near-infrared imagery from relatively low-cost modified sensors for heritage digitization, alongside the usefulness of spectral textures produced, oriented towards heritage science. Therefore, thorough experimentation and assessment with different software are conducted and presented, utilizing NIR imagery and SfM/MVS methods. Dense 3D point clouds and textured meshes have been produced and evaluated for their metric validity and radiometric quality, comparing to results produced from VIS imagery. The datasets employed come from heritage assets of different dimensions, from an archaeological site to a medium-sized artwork, to evaluate implementation on different levels of accuracy and specifications of texture resolution.

scholarly journals Rapid and economic fabrication approach of dielectric reflectors for energy harvesting applications

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Venkatesh Yepuri ◽  
R. S. Dubey ◽  
Brijesh Kumar
Keyword(s):  
Near Infrared ◽  
Low Cost ◽  
Thermal Response ◽  
Wavelength Region ◽  
Infrared Light ◽  
Optical Instruments ◽  
Rapid Fabrication ◽  
Minimum Number ◽  
Annealing Cycle ◽  
Band Pass

Abstract Dielectric reflectors are the passive components that have their potential demands for various purposes, such as back-end reflector in solar cells, the band pass filters in optical instruments, thermal reflector and so on. Though well-established techniques for manufacturing such reflectors are available, the demand for their low-cost production with a minimum number of coatings has attracted the attention of the scientific community. In this framework, this paper addresses the process optimization for the low-cost and rapid fabrication of dielectric TiO2/SiO2 reflectors with 100% reflectance. Numerous studies are carried out to explore the structural, morphological, and optical characteristics of reflectors. We summarize that the desired reflection band of a selective-wavelength range can be realized by varying the precursor and catalyst concentrations, annealing cycle, and the spin rate. With this, we noticed the shifting of reflection window from the visible (Vis) to near-infrared (NIR) wavelength region using reflectors of merely 2.5 stacks of TiO2/SiO2 films. We also performed the thermal response of the reflector by radiating an infrared light source and observed an exceptional performance indicating its thermal shielding application.

Portable multispectral imaging system based on Raspberry Pi

Sensor Review ◽  
2017 ◽  
Vol 37 (3) ◽  
pp. 322-329 ◽  
Author(s):  
Nuria Lopez-Ruiz ◽  
Fernando Granados-Ortega ◽  
Miguel Angel Carvajal ◽  
Antonio Martinez-Olmos
Keyword(s):  
Near Infrared ◽  
Multispectral Imaging ◽  
Imaging System ◽  
Light Emitting Diode ◽  
Low Cost ◽  
Image Sensor ◽  
Raspberry Pi ◽  
Image Processing Algorithm ◽  
Content Type

Purpose In this work, the authors aim to present a compact low-cost and portable spectral imaging system for general purposes. The developed system provides information that can be used for a fast in situ identification and classification of samples based on the analysis of captured images. The connectivity of the instrument allows a deeper analysis of the images in an external computer. Design/methodology/approach The wavelength selection of the system is carried out by light multiplexing through a light-emitting diode panel where eight wavelengths covering the spectrum from ultraviolet (UV) to near-infrared region (NIR) have been included. The image sensor used is a red green blue – infrared (RGB-IR) micro-camera controlled by a Raspberry Pi board where a basic image processing algorithm has been programmed. It allows the visualization in an integrated display of the reflectance and the histogram of the images at each wavelength, including UV and NIRs. Findings The prototype has been tested by analyzing several samples in a variety of applications such as detection of damaged, over-ripe and sprayed fruit, classification of different type of plastic materials and determination of properties of water. Originality/value The designed system presents some advantages as being non-expensive and portable in comparison to other multispectral imaging systems. The low-cost and size of the camera module connected to the Raspberry Pi provides a compact instrument for general purposes.

Automated Detection of Bleeding in Capsule Endoscopy using on-chip Multispectral Imaging Sensors

2020 ◽  
pp. 1-1
Author(s):  
Mohammad Reza Mohebbian ◽  
Md Hanif Ali Sohag ◽  
Seyed Shahim Vedaei ◽  
Khan A. Wahid
Keyword(s):  
Capsule Endoscopy ◽  
Multispectral Imaging ◽  
Automated Detection ◽  
On Chip ◽  
Imaging Sensors

scholarly journals Characterization and mapping of hematite ore mineral classes using hyperspectral remote sensing technique: a case study from Bailadila iron ore mining region

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Ibrahim Shaik ◽  
S. K. Begum ◽  
P. V. Nagamani ◽  
Narayan Kayet
Keyword(s):  
Infrared Absorption ◽  
Near Infrared ◽  
Spectral Feature ◽  
Absorption Feature ◽  
X Ray ◽  
Remote Sensing Technique ◽  
Ore Minerals ◽  
Feature Fitting ◽  
Hematite Ore

AbstractThe study demonstrates a methodology for mapping various hematite ore classes based on their reflectance and absorption spectra, using Hyperion satellite imagery. Substantial validation is carried out, using the spectral feature fitting technique, with the field spectra measured over the Bailadila hill range in Chhattisgarh State in India. The results of the study showed a good correlation between the concentration of iron oxide with the depth of the near-infrared absorption feature (R2 = 0.843) and the width of the near-infrared absorption feature (R2 = 0.812) through different empirical models, with a root-mean-square error (RMSE) between < 0.317 and < 0.409. The overall accuracy of the study is 88.2% with a Kappa coefficient value of 0.81. Geochemical analysis and X-ray fluorescence (XRF) of field ore samples are performed to ensure different classes of hematite ore minerals. Results showed a high content of Fe > 60 wt% in most of the hematite ore samples, except banded hematite quartzite (BHQ) (< 47 wt%).

scholarly journals Metalorganic chemical vapor deposition of InN quantum dots and nanostructures

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Caroline E. Reilly ◽  
Stacia Keller ◽  
Shuji Nakamura ◽  
Steven P. DenBaars
Keyword(s):  
Quantum Dots ◽  
Chemical Vapor Deposition ◽  
Vapor Deposition ◽  
Metalorganic Chemical Vapor Deposition ◽  
Near Infrared ◽  
Optoelectronic Devices ◽  
Chemical Vapor ◽  
Electromagnetic Spectrum ◽  
Material System ◽  
Metalorganic Chemical

AbstractUsing one material system from the near infrared into the ultraviolet is an attractive goal, and may be achieved with (In,Al,Ga)N. This III-N material system, famous for enabling blue and white solid-state lighting, has been pushing towards longer wavelengths in more recent years. With a bandgap of about 0.7 eV, InN can emit light in the near infrared, potentially overlapping with the part of the electromagnetic spectrum currently dominated by III-As and III-P technology. As has been the case in these other III–V material systems, nanostructures such as quantum dots and quantum dashes provide additional benefits towards optoelectronic devices. In the case of InN, these nanostructures have been in the development stage for some time, with more recent developments allowing for InN quantum dots and dashes to be incorporated into larger device structures. This review will detail the current state of metalorganic chemical vapor deposition of InN nanostructures, focusing on how precursor choices, crystallographic orientation, and other growth parameters affect the deposition. The optical properties of InN nanostructures will also be assessed, with an eye towards the fabrication of optoelectronic devices such as light-emitting diodes, laser diodes, and photodetectors.

scholarly journals Feasibility of Using VIS/NIR Spectroscopy and Multivariate Analysis for Pesticide Residue Detection in Tomatoes

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 196
Author(s):  
Araz Soltani Nazarloo ◽  
Vali Rasooli Sharabiani ◽  
Yousef Abbaspour Gilandeh ◽  
Ebrahim Taghinezhad ◽  
Mariusz Szymanek ◽  
...  
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Low Cost ◽  
Moving Average ◽  
Nir Spectroscopy ◽  
Control Treatment ◽  
Residue Detection ◽  
Non Destructive ◽  
Reflective Spectroscopy

The purpose of this work was to investigate the detection of the pesticide residual (profenofos) in tomatoes by using visible/near-infrared spectroscopy. Therefore, the experiments were performed on 180 tomato samples with different percentages of profenofos pesticide (higher and lower values than the maximum residual limit (MRL)) as compared to the control (no pesticide). VIS/near infrared (NIR) spectral data from pesticide solution and non-pesticide tomato samples (used as control treatment) impregnated with different concentrations of pesticide in the range of 400 to 1050 nm were recorded by a spectrometer. For classification of tomatoes with pesticide content at lower and higher levels of MRL as healthy and unhealthy samples, we used different spectral pre-processing methods with partial least squares discriminant analysis (PLS-DA) models. The Smoothing Moving Average pre-processing method with the standard error of cross validation (SECV) = 4.2767 was selected as the best model for this study. In addition, in the calibration and prediction sets, the percentages of total correctly classified samples were 90 and 91.66%, respectively. Therefore, it can be concluded that reflective spectroscopy (VIS/NIR) can be used as a non-destructive, low-cost, and rapid technique to control the health of tomatoes impregnated with profenofos pesticide.

scholarly journals Atmospheric Compensation of PRISMA Data by Means of a Learning Based Approach

2021 ◽  
Vol 13 (15) ◽  
pp. 2967
Author(s):  
Nicola Acito ◽  
Marco Diani ◽  
Gregorio Procissi ◽  
Giovanni Corsini
Keyword(s):  
Spectral Range ◽  
Near Infrared ◽  
Random Noise ◽  
Synthetic Data ◽  
Regression Function ◽  
Short Wave ◽  
Hyperspectral Data ◽  
Electromagnetic Spectrum ◽  
Great Opportunity ◽  
Atmospheric Compensation

Atmospheric compensation (AC) allows the retrieval of the reflectance from the measured at-sensor radiance and is a fundamental and critical task for the quantitative exploitation of hyperspectral data. Recently, a learning-based (LB) approach, named LBAC, has been proposed for the AC of airborne hyperspectral data in the visible and near-infrared (VNIR) spectral range. LBAC makes use of a parametric regression function whose parameters are learned by a strategy based on synthetic data that accounts for (1) a physics-based model for the radiative transfer, (2) the variability of the surface reflectance spectra, and (3) the effects of random noise and spectral miscalibration errors. In this work we extend LBAC with respect to two different aspects: (1) the platform for data acquisition and (2) the spectral range covered by the sensor. Particularly, we propose the extension of LBAC to spaceborne hyperspectral sensors operating in the VNIR and short-wave infrared (SWIR) portion of the electromagnetic spectrum. We specifically refer to the sensor of the PRISMA (PRecursore IperSpettrale della Missione Applicativa) mission, and the recent Earth Observation mission of the Italian Space Agency that offers a great opportunity to improve the knowledge on the scientific and commercial applications of spaceborne hyperspectral data. In addition, we introduce a curve fitting-based procedure for the estimation of column water vapor content of the atmosphere that directly exploits the reflectance data provided by LBAC. Results obtained on four different PRISMA hyperspectral images are presented and discussed.

Sign in / Sign up

Export Citation Format

Share Document