scholarly journals Sensitivity Improvement of Extremely Low Light Scenes with RGB-NIR Multispectral Filter Array Sensor

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1256
Author(s):  
Seunghoon Jee ◽  
Moon Gi Kang
Keyword(s):  
Near Infrared ◽  
Signal To Noise Ratio ◽  
High Sensitivity ◽  
Color Channel ◽  
Low Light ◽  
Pixel Resolution ◽  
Edge Preserving ◽  
Linear Coefficient ◽  
Reconstruction Methods ◽  
Color Channels

Recently, several red-green-blue near-infrared (RGB-NIR) multispectral filter arrays (MFAs), which include near infrared (NIR) pixels, have been proposed. For extremely low light scenes, the RGB-NIR MFA sensor has been extended to receive NIR light, by adding NIR pixels to supplement for the insufficient visible band light energy. However, the resolution reconstruction of the RGB-NIR MFA, using demosaicing and color restoration methods, is based on the correlation between the NIR pixels and the pixels of other colors; this does not improve the RGB channel sensitivity with respect to the NIR channel sensitivity. In this paper, we propose a color restored image post-processing method to improve the sensitivity and resolution of an RGB-NIR MFA. Although several linear regression based color channel reconstruction methods have taken advantage of the high sensitivity NIR channel, it is difficult to accurately estimate the linear coefficients because of the high level of noise in the color channels under extremely low light conditions. The proposed method solves this problem in three steps: guided filtering, based on the linear similarity between the NIR and color channels, edge preserving smoothing to improve the accuracy of linear coefficient estimation, and residual compensation for lost spatial resolution information. The results show that the proposed method is effective, while maintaining the NIR pixel resolution characteristics, and improving the sensitivity in terms of the signal-to-noise ratio by approximately 13 dB.

scholarly journals High Sensitivity Continuous Monitoring of Chloroform Gas by Using Wavelength Modulation Photoacoustic Spectroscopy in the Near-Infrared Range

2021 ◽  
Vol 11 (15) ◽  
pp. 6992
Author(s):  
Tie Zhang ◽  
Yuxin Xing ◽  
Gaoxuan Wang ◽  
Sailing He
Keyword(s):  
Photoacoustic Spectroscopy ◽  
Continuous Monitoring ◽  
Near Infrared ◽  
Resonant Cavity ◽  
High Sensitivity ◽  
Industrial Applications ◽  
Detection Sensitivity ◽  
Infrared Range ◽  
Wavelength Modulation ◽  
Linear Coefficient

An optical system for gaseous chloroform (CHCl3) detection based on wavelength modulation photoacoustic spectroscopy (WMPAS) is proposed for the first time by using a distributed feedback (DFB) laser with a center wavelength of 1683 nm where chloroform has strong and complex absorption peaks. The WMPAS sensor developed possesses the advantages of having a simple structure, high-sensitivity, and direct measurement. A resonant cavity made of stainless steel with a resonant frequency of 6390 Hz was utilized, and eight microphones were located at the middle of the resonator at uniform intervals to collect the sound signal. All of the devices were integrated into an instrument box for practical applications. The performance of the WMPAS sensor was experimentally demonstrated with the measurement of different concentrations of chloroform from 63 to 625 ppm. A linear coefficient R2 of 0.999 and a detection sensitivity of 0.28 ppm with a time period of 20 s were achieved at room temperature (around 20 °C) and atmosphere pressure. Long-time continuous monitoring for a fixed concentration of chloroform gas was carried out to demonstrate the excellent stability of the system. The performance of the system shows great practical value for the detection of chloroform gas in industrial applications.

Low-frequency multiplex CARS microscopy with a high-repetition near-infrared supercontinuum laser

2021 ◽  
Author(s):  
Yusuke Arashida ◽  
Atsushi Taninaka ◽  
Takayuki Ochiai ◽  
Hiroyuki Mogi ◽  
Shoji YOSHIDA ◽  
...  
Keyword(s):  
Near Infrared ◽  
High Efficiency ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
High Sensitivity ◽  
High Repetition ◽  
Spectrum Shaping ◽  
Crystal Phase Transition ◽  
Wavenumber Region ◽  
Anti Stokes

Abstract We have developed a multiplex Coherent anti-Stokes Raman scattering (CARS) microscope effective for low-wavenumber measurement by combining a high-repetition supercontinuum light source of 1064 nm and an infrared high-sensitivity InGaAs diode array. This system could observe the low-wavenumber region down to 55 cm-1 with high sensitivity. In addition, using spectrum shaping and spectrum modulation techniques, we simultaneously realized a wide bandwidth (<1800 cm-1), high wavenumber resolution (9 cm-1), high efficiency, and increasing signal to noise ratio by reducing the effect of the background shape in low-wavenumber region. Spatial variation of a sulfur crystal phase transition with metastable states was visualized.

scholarly journals Sound Out the Deep Colors: Photoacoustic Molecular Imaging at New Depths

2020 ◽  
Vol 19 ◽  
pp. 153601212098151
Author(s):  
Mucong Li ◽  
Nikhila Nyayapathi ◽  
Hailey I. Kilian ◽  
Jun Xia ◽  
Jonathan F. Lovell ◽  
...  
Keyword(s):  
Molecular Imaging ◽  
Near Infrared ◽  
High Sensitivity ◽  
Biological Tissues ◽  
Molecular Probes ◽  
Cellular Processes ◽  
Reconstruction Methods ◽  
Recent Developments ◽  
Imaging Depth ◽  
Molecular Signals

Photoacoustic tomography (PAT) has become increasingly popular for molecular imaging due to its unique optical absorption contrast, high spatial resolution, deep imaging depth, and high imaging speed. Yet, the strong optical attenuation of biological tissues has traditionally prevented PAT from penetrating more than a few centimeters and limited its application for studying deeply seated targets. A variety of PAT technologies have been developed to extend the imaging depth, including employing deep-penetrating microwaves and X-ray photons as excitation sources, delivering the light to the inside of the organ, reshaping the light wavefront to better focus into scattering medium, as well as improving the sensitivity of ultrasonic transducers. At the same time, novel optical fluence mapping algorithms and image reconstruction methods have been developed to improve the quantitative accuracy of PAT, which is crucial to recover weak molecular signals at larger depths. The development of highly-absorbing near-infrared PA molecular probes has also flourished to provide high sensitivity and specificity in studying cellular processes. This review aims to introduce the recent developments in deep PA molecular imaging, including novel imaging systems, image processing methods and molecular probes, as well as their representative biomedical applications. Existing challenges and future directions are also discussed.

Tropical Cyclone Characterization via Nocturnal Low-Light Visible Illumination

2017 ◽  
Vol 98 (11) ◽  
pp. 2351-2365 ◽  
Author(s):  
Jeffrey D. Hawkins ◽  
Jeremy E. Solbrig ◽  
Steven D. Miller ◽  
Melinda Surratt ◽  
Thomas F. Lee ◽  
...  
Keyword(s):  
Near Infrared ◽  
Infrared Imaging ◽  
Image Interpretation ◽  
High Sensitivity ◽  
Lunar Cycle ◽  
Digital Data ◽  
Light Illumination ◽  
Infrared Band ◽  
Low Light ◽  
Intensity Changes

Abstract Global monitoring of tropical cyclones (TC) is enhanced by the unique capabilities provided by the day–night band (DNB), a sensor included on the Visible Infrared Imaging Radiometer Suite (VIIRS) flying on board the Suomi National Polar-Orbiting Partnership (SNPP) satellite. The DNB, a low-light visible–near-infrared-band passive radiometer, can leverage unconventional (i.e., nonsolar) sources of visible light illumination such as moonlight to infer storm structure at night. The DNB provides an unprecedented capability to resolve moonlit clouds at high resolution, offering numerous potential benefits to both operational TC analysts and researchers developing new methods of monitoring TCs occurring within the largely data-void tropical oceanic basins. DNB digital data provide significant enhancements over older nighttime visible data from the Defense Meteorological Satellite Program’s (DMSP) Operational Linescan System (OLS) by leveraging accurate calibration, high sensitivity, and sub-kilometer-scale imagery that covers 2–3 times the moon’s lunar cycle than the OLS. By leveraging these attributes, DNB data can enable the use of automated objective applications instead of subjective image interpretation. Here, the authors detail ways in which critical information about TC structure, location, intensity changes, shear environment, lightning, and other characteristics can be extracted when the DNB data are used in isolation or in a multichannel approach with coincident infrared (IR) channels.

scholarly journals Physical noise propagation in color image construction: a geometrical interpretation

2019 ◽  
Vol 2019 (1) ◽  
pp. 375-380
Author(s):  
Axel Clouet ◽  
Jérôme Vaillant ◽  
David Alleysson
Keyword(s):  
Near Infrared ◽  
Color Image ◽  
Signal To Noise Ratio ◽  
Point Of View ◽  
Signal To Noise ◽  
Low Light ◽  
Image Construction ◽  
Color Sensor ◽  
Light Sensor ◽  
Noise Ratio

To avoid false colors, classical color sensors cut infrared wavelengths for which silicon is sensitive (with the use of an infrared cutoff filter called IR-cut). However, in low light situation, noise can alter images. To increase the amount of photons received by the sensor, in other words, the sensor's sensitivity, it has been proposed to remove the IR-cut for low light applications. In this paper, we analyze if this methodology is beneficial from a signal to noise ratio point of view when the wanted result is a color image. For this aim we recall the formalism behind physical raw image acquisition and color reconstruction. A comparative study is carried out between one classical color sensor and one specific color sensor designed for low light conditions. Simulated results have been computed for both sensors under same exposure settings and show that raw signal to noise ratio is better for the low light sensor. However, its reconstructed color image appears more noisy. Our formalism illustrates geometrically the reasons of this degradation in the case of the low light sensor. It is due on one hand to the higher correlation between spectral channels and on the other hand to the near infrared part of the signal in the raw data which is not intrinsically useful for color.

scholarly journals The Influence of Shadow Effects on the Spectral Characteristics of Glacial Meltwater

2020 ◽  
Vol 13 (1) ◽  
pp. 36
Author(s):  
Kornelia Anna Wójcik-Długoborska ◽  
Robert Józef Bialik
Keyword(s):  
Spectral Properties ◽  
Satellite Images ◽  
Near Infrared ◽  
Spectral Band ◽  
Spectral Characteristics ◽  
High Sensitivity ◽  
Surface Model ◽  
Landsat 8 ◽  
Pixel Resolution ◽  
Ice Phenomena

The phenomenon of shadows due to glaciers is investigated in Antarctica. The observed shadow effect disrupts analyses conducted by remote sensing and is a challenge in the assessment of sediment meltwater plumes in polar marine environments. A DJI Inspire 2 drone equipped with a Zenmuse x5s camera was used to generate a digital surface model (DSM) of 6 King George Island glaciers: Ecology, Dera, Zalewski, Ladies, Krak, and Vieville. On this basis, shaded areas of coves near glaciers were traced. For the first time, spectral characteristics of shaded meltwater were observed with the simultaneous use of a Sequoia+ spectral camera mounted on a Parrot Bluegrass drone and in Landsat 8 satellite images. In total, 44 drone flights were made, and 399 satellite images were analyzed. Among them, four drone spectral images and four satellite images were selected, meeting the condition of a visible shadow. For homogeneous waters (deep, low turbidity, without ice phenomena), the spectral properties tend to change during the approach to an obstacle casting a shadow especially during low shortwave downward radiation. In this case, in the shade, the amount of radiation reflected in the green spectral band decreases by 50% far from the obstacle and by 43% near the obstacle, while in near infrared (NIR), it decreases by 42% and 21%, respectively. With highly turbid, shallow water and ice phenomena, this tendency does not occur. It was found that the green spectral band had the highest contrast in the amount of reflected radiation between nonshaded and shaded areas, but due to its high sensitivity, the analysis could have been overestimated. The spectral properties of shaded meltwater differ depending on the distance from the glacier front, which is related to the saturation of the water with sediment particles. We discovered that the pixel aggregation of uniform areas caused the loss of detailed information, while pixel aggregation of nonuniform, shallow areas with ice phenomena caused changes and the loss of original information. During the aggregation of the original pixel resolution (15 cm) up to 30 m, the smallest error occurred in the area with a homogeneous water surface, while the greatest error (over 100%) was identified in the places where the water was strongly cloudy or there were ice phenomena.

Pre-Processing of Hyperspectral Images Using Nonlinear Filters

2013 ◽  
Vol 11 (1) ◽  
pp. 8-13
Author(s):  
V. Behar ◽  
V. Bogdanova
Keyword(s):  
Signal To Noise Ratio ◽  
Correlation Coefficients ◽  
Hyperspectral Images ◽  
Spectral Correlation ◽  
Edge Preserving ◽  
Improvement Factor ◽  
Filter Output ◽  
Average Improvement ◽  
Processing Procedure

Abstract In this paper the use of a set of nonlinear edge-preserving filters is proposed as a pre-processing stage with the purpose to improve the quality of hyperspectral images before object detection. The capability of each nonlinear filter to improve images, corrupted by spatially and spectrally correlated Gaussian noise, is evaluated in terms of the average Improvement factor in the Peak Signal to Noise Ratio (IPSNR), estimated at the filter output. The simulation results demonstrate that this pre-processing procedure is efficient only in case the spatial and spectral correlation coefficients of noise do not exceed the value of 0.6

scholarly journals Multi-Feature Guided Low-Light Image Enhancement

2021 ◽  
Vol 11 (11) ◽  
pp. 5055
Author(s):  
Hong Liang ◽  
Ankang Yu ◽  
Mingwen Shao ◽  
Yuru Tian
Keyword(s):  
Image Enhancement ◽  
Signal To Noise Ratio ◽  
Low Light ◽  
Low Contrast ◽  
Light Image ◽  
Affine Model ◽  
The Neural Network ◽  
Low Visibility ◽  
Model Robustness ◽  
Traditional Image

Due to the characteristics of low signal-to-noise ratio and low contrast, low-light images will have problems such as color distortion, low visibility, and accompanying noise, which will cause the accuracy of the target detection problem to drop or even miss the detection target. However, recalibrating the dataset for this type of image will face problems such as increased cost or reduced model robustness. To solve this kind of problem, we propose a low-light image enhancement model based on deep learning. In this paper, the feature extraction is guided by the illumination map and noise map, and then the neural network is trained to predict the local affine model coefficients in the bilateral space. Through these methods, our network can effectively denoise and enhance images. We have conducted extensive experiments on the LOL datasets, and the results show that, compared with traditional image enhancement algorithms, the model is superior to traditional methods in image quality and speed.

scholarly journals The Double Face of Ketamine—The Possibility of Its Identification in Blood and Beverages

Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 813
Author(s):  
Magdalena Świądro ◽  
Paweł Stelmaszczyk ◽  
Irena Lenart ◽  
Renata Wietecha-Posłuszny
Keyword(s):  
Date Rape ◽  
Signal To Noise Ratio ◽  
High Sensitivity ◽  
Heroin Addiction ◽  
Assisted Extraction ◽  
Low Concentrations ◽  
High Concentrations ◽  
Rosé Wine ◽  
Tof Ms

The purpose of this study was to develop and validate a high-sensitivity methodology for identifying one of the most used drugs—ketamine. Ketamine is used medicinally to treat depression, alcoholism, and heroin addiction. Moreover, ketamine is the main ingredient used in so-called “date-rape” pills (DRP). This study presents a novel methodology for the simultaneous determination of ketamine based on the Dried Blood Spot (DBS) method, in combination with capillary electrophoresis coupled with a mass spectrometer (CE-TOF-MS). Then, 6-mm circles were punched out from DBS collected on Whatman DMPK-C paper and extracted using microwave-assisted extraction (MAE). The assay was linear in the range of 25–300 ng/mL. Values of limits of detection (LOD = 6.0 ng/mL) and quantification (LOQ = 19.8 ng/mL) were determined based on the signal to noise ratio. Intra-day precision at each determined concentration level was in the range of 6.1–11.1%, and inter-day between 7.9–13.1%. The obtained precision was under 15.0% (for medium and high concentrations) and lower than 20.0% (for low concentrations), which are in accordance with acceptance criteria. Therefore, the DBS/MAE/CE-TOF-MS method was successfully checked for analysis of ketamine in matrices other than blood, i.e., rose wine and orange juice. Moreover, it is possible to identify ketamine in the presence of flunitrazepam, which is the other most popular ingredient used in DRP. Based on this information, the selectivity of the proposed methodology for identifying ketamine in the presence of other components of rape pills was checked.

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