Face synthesis from near-infrared to visual light spectrum using quotient image and kernel-based multifactor analysis

2011 ◽  
Author(s):  
Zeda Zhang ◽  
Yunhong Wang ◽  
Zhaoxiang Zhang ◽  
Guangpeng Zhang
Keyword(s):  
Near Infrared ◽  
Light Spectrum ◽  
Multifactor Analysis ◽  
Face Synthesis ◽  
Visual Light

scholarly journals Classifying Reflectance Targets under Ambient Light Conditions Using Passive Spectral Measurements

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5375
Author(s):  
Ali Hamidisepehr ◽  
Michael P. Sama ◽  
Joseph S. Dvorak ◽  
Ole O. Wendroth ◽  
Michael D. Montross
Keyword(s):  
Spectral Data ◽  
Prediction Accuracy ◽  
Near Infrared ◽  
Machine Learning Algorithms ◽  
Spectral Signature ◽  
Integration Time ◽  
Ambient Light ◽  
Light Conditions ◽  
Light Spectrum ◽  
Compensation Methods

Collecting remotely sensed spectral data under varying ambient light conditions is challenging. The objective of this study was to test the ability to classify grayscale targets observed by portable spectrometers under varying ambient light conditions. Two sets of spectrometers covering ultraviolet (UV), visible (VIS), and near−infrared (NIR) wavelengths were instrumented using an embedded computer. One set was uncalibrated and used to measure the raw intensity of light reflected from a target. The other set was calibrated and used to measure downwelling irradiance. Three ambient−light compensation methods that successively built upon each other were investigated. The default method used a variable integration time that was determined based on a previous measurement to maximize intensity of the spectral signature (M1). The next method divided the spectral signature by the integration time to normalize the spectrum and reveal relative differences in ambient light intensity (M2). The third method divided the normalized spectrum by the ambient light spectrum on a wavelength basis (M3). Spectral data were classified using a two−step process. First, raw spectral data were preprocessed using a partial least squares (PLS) regression method to compress highly correlated wavelengths and to avoid overfitting. Next, an ensemble of machine learning algorithms was trained, validated, and tested to determine the overall classification accuracy of each algorithm. Results showed that simply maximizing sensitivity led to the best prediction accuracy when classifying known targets. Average prediction accuracy across all spectrometers and compensation methods exceeded 93%.

scholarly journals Colored Paints Containing NIR-Reflective Pigments Exposed to Accelerated Ultraviolet Radiation Aging with Possible Application as Roof Coatings

Coatings ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1135
Author(s):  
Stefano Rossi ◽  
Hampus Lindmark ◽  
Michele Fedel
Keyword(s):  
Near Infrared ◽  
Light Exposure ◽  
Maximum Temperature ◽  
Potential Candidate ◽  
Light Spectrum ◽  
Ir Camera ◽  
Color Changes ◽  
The Difference ◽  
Steel Panels ◽  
The Stability

This study aims to evaluate the difference in thermal behavior among paints with the presence of traditional and NIR pigments by means of a simple and cheap laboratory-scale test. Considering these goals, the thermal and esthetical properties of two different cool coatings were assessed, highlighting their positive and limited aspects. Two different complex near-infrared inorganic reflective (NIR) pigments with yellow and black respectably colors were mixed in an acrylic waterborne copolymer binder. The paint formulations were applied on steel panels. The thermal performance of the coatings was investigated in the NIR-region of the light spectrum by exposing the samples to an IR-lamp. The outer and inner surface temperatures of the painted panels were recorded using thermocouples and an IR camera. The samples were aged by artificial UV-B light exposure. Color and specular gloss changes at different exposure times were evaluated. The behavior of the cool coatings was compared with that of conventional coatings with similar color characteristics. The black cool coating achieved a maximum temperature decrease, compared to the conventional black one, of approximately 12 °C. The stability for the cool coatings was very similar to that of the conventional coating, indicating that black pigment could be a potential candidate for cool-coating applications. The yellow cool coatings did not show a significant decrease in temperature compared to the conventional paint. The gloss and color changes resulted as influenced by the types and amount of pigments.

scholarly journals Effects of Epiphytes and Depth on Seagrass Spectral Profiles: Case Study of Gulf St. Vincent, South Australia

2019 ◽  
Vol 16 (15) ◽  
pp. 2701 ◽  
Author(s):  
Charnsmorn Hwang ◽  
Chih-Hua Chang ◽  
Michael Burch ◽  
Milena Fernandes ◽  
Tim Kildea
Keyword(s):  
Remote Sensing ◽  
Natural Resource ◽  
Near Infrared ◽  
Rapid Change ◽  
South Australia ◽  
Light Spectrum ◽  
Coastal Marine ◽  
Spectral Profiles ◽  
Coastal Marine Ecosystems

Seagrasses are a crucial indicator species of coastal marine ecosystems that provide substratum, shelter, and food for epiphytic algae, invertebrates, and fishes. More accurate mapping of seagrasses is essential for their survival as a long-lasting natural resource. Before reflectance spectra could properly be used as remote sensing endmembers, factors that may obscure the detection of reflectance signals must be assessed. The objectives in this study are to determine the influence of (1) epiphytes, (2) water depth, and (3) seagrass genus on the detection of reflectance spectral signals. The results show that epiphytes significantly dampen bottom-type reflectance throughout most of the visible light spectrum, excluding 670–679 nm; the depth does influence reflectance, with the detection of deeper seagrasses being easier, and as the depth increases, only Heterozostera increase in the exact “red edge” wavelength at which there is a rapid change in the near-infrared (NIR) spectrum. These findings helped improve the detection of seagrass endmembers during remote sensing, thereby helping protect the natural resource of seagrasses.

Effect of heat treatment on the reflective spectrum of zinc oxide powders

2009 ◽  
Vol 24 (1) ◽  
pp. 19-23 ◽  
Author(s):  
M.M. Mikhailov ◽  
V.V. Neshchimenko ◽  
Chundong Li ◽  
Shiyu He ◽  
Dezhuang Yang
Keyword(s):  
Heat Treatment ◽  
Zinc Oxide ◽  
Spectral Reflectance ◽  
Near Infrared ◽  
Thermal Control ◽  
Infrared Region ◽  
Light Spectrum ◽  
Absorption Bands ◽  
Oxide Powders ◽  
Reflective Spectrum

To determine the optimum baking temperatures for nanopowder introduction, the variation of reflective spectrum of baked zinc oxide powders, which are used as pigments for thermal control coatings of spacecraft, has been investigated over the wavelength range of 0.225–2.5 μm after being baked at temperatures between 400 °C and 850 °C. It has been established that baking temperatures over 750 °C result in a reduction of spectral reflectance in the visible light spectrum region. This is due to the formation of absorption bands of intrinsic point defects and thus increasing the spectral reflectance in the near-infrared region. The optimum temperature is 650 °C at which the bleaching effect was observed long after heat treatment. Moreover, an increase in the reflection coefficient occurs in the regions of 380–450 nm and 1100–2500 nm in this case.

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