Methods to improve colour mismatch between displays

2021 ◽  
Vol 2021 (29) ◽  
pp. 37-41
Author(s):  
Keyu Shi ◽  
Ming Ronnier Luo
Keyword(s):  
Power Distribution ◽  
Spectral Power ◽  
Rapid Development ◽  
Correction Method ◽  
Spectral Power Distribution ◽  
Lcd Display ◽  
Display Technology ◽  
Tristimulus Values ◽  
Colorimetric Data ◽  
The Difference

With the rapid development of display technology, the colour mismatch of the colours having same tristimulus values between devices is an urgent problem to be solved. This is related to the wellknown problem of observer metamerism, caused by the spectral power distribution (SPD) of primaries and the difference between individual observers' and the standard CIE colour matching functions. An experiment was carried out for 20 observers to perform colour matching of colour stimuli with a field-of-view of 4° between 5 displays, including two LCD and two OLED, against a reference LCD display. The results were used to derive a matrixbased colour correction method. The method was derived from colorimetric visually matched colorimetric data. Furthermore, different colour matching functions were evaluated to predict the degree of observer metamerism. The results showed that the correction method gave satisfactory results. Finally, it was found that the use of 2006 2° colour matching function outperformed 1931 2° CMFs with a large margin, most marked between an OLED and an LCD display.

scholarly journals A Toolbox and Crowdsourcing Platform for Automatic Labeling of Independent Components in Electroencephalography

2021 ◽  
Vol 15 ◽  
Author(s):  
Gurgen Soghoyan ◽  
Alexander Ledovsky ◽  
Maxim Nekrashevich ◽  
Olga Martynova ◽  
Irina Polikanova ◽  
...  
Keyword(s):  
Power Distribution ◽  
Spectral Power ◽  
Supervised Machine Learning ◽  
Mu Rhythm ◽  
Artifact Detection ◽  
Independent Components ◽  
Spectral Power Distribution ◽  
Brain Signals ◽  
Movement Artifact ◽  
The Difference

Independent Component Analysis (ICA) is a conventional approach to exclude non-brain signals such as eye movements and muscle artifacts from electroencephalography (EEG). A rejection of independent components (ICs) is usually performed in semiautomatic mode and requires experts’ involvement. As also revealed by our study, experts’ opinions about the nature of a component often disagree, highlighting the need to develop a robust and sustainable automatic system for EEG ICs classification. The current article presents a toolbox and crowdsourcing platform for Automatic Labeling of Independent Components in Electroencephalography (ALICE) available via link http://alice.adase.org/. The ALICE toolbox aims to build a sustainable algorithm to remove artifacts and find specific patterns in EEG signals using ICA decomposition based on accumulated experts’ knowledge. The difference from previous toolboxes is that the ALICE project will accumulate different benchmarks based on crowdsourced visual labeling of ICs collected from publicly available and in-house EEG recordings. The choice of labeling is based on the estimation of IC time-series, IC amplitude topography, and spectral power distribution. The platform allows supervised machine learning (ML) model training and re-training on available data subsamples for better performance in specific tasks (i.e., movement artifact detection in healthy or autistic children). Also, current research implements the novel strategy for consentient labeling of ICs by several experts. The provided baseline model could detect noisy IC and components related to the functional brain oscillations such as alpha and mu rhythm. The ALICE project implies the creation and constant replenishment of the IC database, which will improve ML algorithms for automatic labeling and extraction of non-brain signals from EEG. The toolbox and current dataset are open-source and freely available to the researcher community.

scholarly journals A Toolbox and Crowdsourcing Platform for Automatic Labeling of Independent Components in Electroencephalography (ALICE)

2021 ◽  
Author(s):  
Gurgen Soghoyan ◽  
Alexander Ledovsky ◽  
Maksim Nekrashevich ◽  
Olga Martynova ◽  
Irina Polikanova ◽  
...  
Keyword(s):  
Power Distribution ◽  
Spectral Power ◽  
Mu Rhythm ◽  
Artifact Detection ◽  
Independent Components ◽  
Spectral Power Distribution ◽  
Brain Signals ◽  
Movement Artifact ◽  
The Difference ◽  
Model Training

Independent Component Analysis (ICA) is a conventional approach to exclude non-brain signals such as eye-movements and muscle artifacts from electroencephalography (EEG). Due to other possible EEG contaminations, a rejection of independent components (ICs) is usually performed in semiautomatic mode and requires experts’ involvement. Noteworthy, as also revealed by our study, experts’ opinion about the nature of a component often disagrees highlighting the need to develop a robust and sustainable automatic system for EEG ICs classification. The current article presents a toolbox and crowdsourcing platform for Automatic Labeling of Independent Components in Electroencephalography (ALICE) available via link http://alice.adase.org/. The ALICE toolbox aims to build a sustainable algorithm not only to remove artifacts but also to find specific patterns in EEG signals using ICA decomposition based on accumulated experts’ knowledge.   The difference from previous toolboxes is that the ALICE project will accumulate different benchmarks based on crowdsourced visual labeling of ICs collected from publicly available and in-house EEG recordings. The choice of labeling is based on estimation of IC time-series, IC amplitude topography and spectral power distribution. The platform allows supervised ML model training and re-training on available data subsamples for better performance in specific tasks (i.e. movement artifact detection in healthy or autistic children). Also, current research implements the novel strategy for consentient labeling of ICs by several experts. The provided baseline model shows that it can be used not only for detection of noisy IC but also for automatic identifications of components related to the functional brain oscillations such as alpha and mu-rhythm.   The ALICE project implies the creation and constant replenishment of the IC database, which will be used for continuous improvement of ML algorithms for automatic labeling and extraction of non-brain signals from EEG. The toolbox and current dataset are open-source and freely available to the researcher community.

Supercontinuum laser-based monochromatic radiant source for detector spectral responsivity characterization in the range 0.9–1.6 μm using absolute cryogenic radiometer

2020 ◽  
pp. 28-33
Author(s):  
A. Yu. Dunaev ◽  
A. S. Baturin ◽  
V. N. Krutikov ◽  
S. P. Morozova
Keyword(s):  
Power Distribution ◽  
Spectral Power ◽  
Feedback System ◽  
Operating Mode ◽  
Spectral Responsivity ◽  
Spectral Power Distribution ◽  
Cryogenic Radiometer ◽  
Supercontinuum Laser ◽  
Radiant Power ◽  
Double Monochromator

An improved monochromatic radiant source with spectral bandwidth of 4 nm based on supercontinuum laser and a double monochromator was included in absolute cryogenic radiometer-based facility to improve the accuracy of spectral responsivity measurement in the range 0.9–1.6 μm. The developed feedback system ensures stabilization of monochromatic radiant power with standard deviation up to 0.025 %. Radiant power that proceeds detector under test or absolute cryogenic radiometer varies from 0.1 to 1.5 mW in dependence of wavelength. The spectral power distribution of its monochromatic source for various operating mode is presented.

scholarly journals Influences of Spectral Power Distribution on Circadian Energy, Visual Comfort and Work Performance

2021 ◽  
Vol 13 (9) ◽  
pp. 4852
Author(s):  
Jack Ngarambe ◽  
Inhan Kim ◽  
Geun Young Yun
Keyword(s):  
Light Source ◽  
Power Distribution ◽  
Work Performance ◽  
Spectral Power ◽  
Light Emitting Diode ◽  
Essential Element ◽  
Visual Comfort ◽  
Light Emitting ◽  
Organic Light Emitting Diode ◽  
Spectral Power Distribution

Spectral power distribution (SPD) is an essential element that has considerable implications on circadian energy and the perception of lit environments. The present study assessed the potential influences of SPD on energy consumption (i.e., considering circadian energy), visual comfort, work performance and mood. Two lighting conditions based on light-emitting diode (LED) and organic light-emitting diode (OLED) were used as proxies for SPDs of different spectral content: dominant peak wavelength of 455 nm (LED) and 618 nm (OLED). Using measured photometric values, the circadian light (CL), melatonin suppression (MS), and circadian efficacy (CE) of the two lighting sources were estimated via a circadian-phototransduction model and compared. Additionally, twenty-six participants were asked to evaluate the said lit environments subjectively in terms of visual comfort and self-reported work performance. Regarding circadian lighting and the associated energy implications, the LED light source induced higher biological actions with relatively less energy than the OLED light source. For visual comfort, OLED lighting-based conditions were preferred to LED lighting-based conditions, while the opposite was true when considering work performance and mood. The current study adds to the on-going debate regarding human-centric lighting, particularly considering the role of SPD in energy-efficient and circadian lighting practices.

scholarly journals The spectral power distribution of light and twilight photometry

2017 ◽  
Vol 0 (1) ◽  
pp. 43-52
Author(s):  
Леонід Андрійович Назаренко ◽  
Тетяна Можаровська ◽  
Дмитро Усиченко
Keyword(s):  
Power Distribution ◽  
Spectral Power ◽  
Spectral Power Distribution

LED for hyperspectral imaging – a new selection method

2018 ◽  
Vol 63 (5) ◽  
pp. 529-535 ◽  
Author(s):  
Tobias Heimpold ◽  
Frank Reifegerste ◽  
Stefan Drechsel ◽  
Jens Lienig
Keyword(s):  
Hyperspectral Imaging ◽  
Power Distribution ◽  
Spectral Power ◽  
Selection Process ◽  
Selection Method ◽  
Light Emitting ◽  
Spectral Power Distribution ◽  
Forward Current ◽  
Efficient Selection ◽  
Selection Of

AbstractHyperspectral imaging (HSI) has become a sophisticated technique in modern applications such as food analyses, recycling technology, medicine, pharmacy and forensic science. It allows one to analyse both spatial and spectral information from an object. But hyperspectral cameras are still expensive due to their extended wavelength range. The development of new light-emitting diodes (LED) in the recent past enables another approach to HSI using a monochrome camera in combination with a LED-based illumination. However, such a system has a lower spectral resolution. Additionally, the growing supply of LED on the market complicates the selection of LED. In this paper, we propose a new time efficient selection method for the design process of an illumination. It chooses an optimised LED combination from an existing database to match a predefined spectral power distribution. Therefore, an algorithm is used to evaluate various LED combinations. Furthermore, the method considers the spectral behaviour of each LED in dependence of forward current and temperature of the solder point. Our method has already shown promise during the selection process for even spectral distributions which is demonstrated in the study. Additionally, we will show its potential for HSI illuminations.

AN OVERVIEW OF THE IMPACT OF STRAY LIGHT FROM COMMERCIAL GREENHOUSES

2021 ◽  
Author(s):  
K. Bertin ◽  
G. Zissis ◽  
G. Salas ◽  
P.M. Raynham ◽  
A. Moutsi ◽  
...  
Keyword(s):  
Power Distribution ◽  
Spectral Power ◽  
Stray Light ◽  
Significant Problem ◽  
Light Sources ◽  
Spectral Power Distribution ◽  
Outdoor Work ◽  
Local Residents ◽  
The Impact ◽  
Current Standards

Stray light from commercial greenhouses is becoming a significant problem causing disruption to wildlife activity and annoyance for local residents. To quantify the amount of stray light from a typical large greenhouse the authors have modelled several lighting installations based on a range of generic horticultural light sources. The impact of the stray light is dependent on the spectral power distribution of the sources employed, the intensity and distribution. Current standards for obtrusive light from outdoor work places do not seem to be suitable when applied to greenhouses.

Circadian stimulus – A computation model with photometric and colorimetric quantities

2019 ◽  
Vol 52 (6) ◽  
pp. 751-762
Author(s):  
W Truong ◽  
V Trinh ◽  
TQ Khanh
Keyword(s):  
Power Distribution ◽  
Spectral Power ◽  
External Validation ◽  
Circadian System ◽  
Model Fit ◽  
Light Sources ◽  
Computation Model ◽  
Internal Validation ◽  
Spectral Power Distribution ◽  
Chromaticity Coordinate

The circadian stimulus is an important, validated and updated metric that describes the invisible influences of light on the human circadian system explicitly and scientifically. However, an absolute spectral power distribution must be supplied for its computation, which is only measurable by an expensive and complicated spectrometer. This paper proposes an alternative circadian stimulus computation model that is identified as the function CS(z, Ev) for white light sources based on the most common and simplest parameters of illuminance Ev in lux and the chromaticity coordinate z. These parameters are well known and widely used in both colour science and lighting technology. In order to prove the accuracy and availability of the model, an internal validation was performed with the adapted method repeating split data to check the goodness of the model fit. The fitted model achieved a maximum residual of 0.058 in the circadian stimulus quantity (R2 = 0.998). An external validation with the maximum residual of 0.030 (R2 = 0.999) provided stronger evidence for the usability of the model in applications.

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