Deep learning-assisted common temperature measurement based on visible light imaging

Real-time,contact-free temperature monitoring of low to medium range(30℃-150℃)has been extensively used in industry and agriculture,which is usually realized by costly infrared temperature detection methods.This paper proposes an alternative approach of extracting temperature information in real time from the visible light images of the monitoring target using a convolutional neural network(CNN).A mean-square error of<1.119℃was reached in the temperature measurements of low to medium range using the CNN and the visible light images.Imaging angle and imaging distance do not affect the temperature detection using visible optical images by the CNN.Moreover,the CNN has a certain illuminance generalization ability capable of detection temperature information from the images which were collected under different illuminance and were not used for training.Compared to the conventional machine learning algorithms mentioned in the recent literatures,this real-time,contact-free temperature measurement approach that does not require any further image processing operations facilitates temperature monitoring applications in the industrial and civil fields.

CAEFusion: A New Convolutional Autoencoder-Based Infrared and Visible Light Image Fusion Algorithm

To address the issues of incomplete information,blurred details,loss of details,and insufficient contrast in infrared and visible image fusion,an image fusion algorithm based on a convolutional autoencoder is proposed.The region attention module is meant to extract the background feature map based on the distinct properties of the background feature map and the detail feature map.A multi-scale convolution attention module is suggested to enhance the communication of feature information.At the same time,the feature transformation module is introduced to learn more robust feature representations,aiming to preserve the integrity of image information.This study uses three available datasets from TNO,FLIR,and NIR to perform thorough quantitative and qualitative trials with five additional algorithms.The methods are assessed based on four indicators:information entropy(EN),standard deviation(SD),spatial frequency(SF),and average gradient(AG).Object detection experiments were done on the M3FD dataset to further verify the algorithm’s performance in comparison with five other algorithms.The algorithm’s accuracy was evaluated using the mean average precision at a threshold of 0.5(mAP@0.5)index.Comprehensive experimental findings show that CAEFusion performs well in subjective visual and objective evaluation criteria and has promising potential in downstream object detection tasks.

Photoprotective Ability of Sunscreens against Ultraviolet, Visible Light and Near-Infrared Radiation

Despite the widespread prevalence of daily sunscreen usage, solar-induced skin damage continues to occur. We have previously reported that solar visible light and near-infrared, in addition to ultraviolet radiation, perform as aging factors and induce deleterious effects such as photoaging, vasodilation, muscle thinning, skin ptosis, photoimmunosupression and photocarcinogenesis. Despite this, most commonly used sunscreens only block ultraviolet radiation. To evaluate the complete solar-spectrum blocking ability of sunscreens produced by internationally well-known companies, a double-beam spectrophotometer was used to optically measure the transmission spectra. The spectrophotometer utilizes a unique, single monochromatic design covering a wavelength range of 240 to 2600 nm. Sunscreens (thickness, 0.1 mm, SPF50+, PA+++ or ++++) from internationally well-known companies blocked 78.8% - 99.9% of ultraviolet, 33.4% - 99.6% of visible light, and 27.0% - 76.4% of near-infrared. It can be concluded that while most commercially available sunscreens filter ultraviolet radiation, they are not effective at blocking visible light and near-infrared radiation. The results of this study imply that sunscreens that provide comprehensive photoprotection from ultraviolet through to near-infrared should be considered to prevent skin photodamage.

Novel Low Viscosity Zinc Oxide, Iron Oxides and Erioglaucine Sunscreen Potential to Protect from Ultraviolet, Visible Light and Near-Infrared Radiation

Despite the widespread recommendation and use of sunscreens and ultraviolet blocking materials, solar-induced skin damage and photoageing continues to pose a problem to human health worldwide. We have previously reported that solar visible light and near-infrared also contribute to skin damage and photo ageing. Most commonly recommended sunscreens are only effective throughout the UV spectrum, offering no protection from visible light and near-infrared. A possible solution could be to augment sunscreens with metal oxides which block visible light and near-infrared radiation. To evaluate the enhanced solar-spectrum blocking ability of novel low viscosity sunscreen containing zinc and iron oxides, a double-beam spectrophotometer was used to optically measure the transmission spectra. The spectrophotometer deploys a unique, single monochromatic design to detect wavelength penetration in the range of 240 to 2600 nm. The Sunscreen base without zinc oxide and iron oxides (control) blocked over 80% of ultraviolet-C and ultraviolet-B but did not block ultraviolet-A, visible light, or near-infrared. The novel low viscosity zinc oxide sample blocked almost over 90% ultraviolet, but did not block visible light and near-infrared sufficiently. However, the samples with the novel low viscosity zinc oxide, iron oxides and erioglaucine blocked almost over 90% of ultraviolet, visible light and near-infrared. It can be concluded that this novel combination of low viscosity zinc oxide, iron oxides and erioglaucine is effective at blocking ultraviolet, visible light and near-infrared radiation. The results of this study imply that sunscreens that provide comprehensive photoprotection from ultraviolet through to near-infrared should be adopted to prevent skin photodamage.

Photoprotective Ability of Colored Iron Oxides in Tinted Sunscreens against Ultraviolet, Visible Light and Near-Infrared Radiation

Solar-induced skin damage continues to pose a problem to human health worldwide, despite the widespread recommendation and use of sunscreens. We have previously reported that solar visible light and near-infrared also contribute to skin damage and photoageing. Most commonly recommended sunscreens are only effective throughout the UV spectrum, offering no protection from visible light and near-infrared. To evaluate the enhanced solar-spectrum blocking ability of iron oxides, a double-beam spectrophotometer was used to optically measure the transmission spectra. The spectrophotometer deploys a unique, single monochromatic design to detect wavelength penetration in the range of 240 to 2600 nm. The sample without iron oxide (control) blocked over 80% of ultraviolet-C and ultraviolet-B but did not block ultraviolet-A, visible light, or near-infrared wavelengths. The samples with yellow, and red iron oxide blocked over 90% ultraviolet, but did not block visible light and near-infrared effectively. The sample with black iron oxide blocked visible light, and near-infrared effectively compared with other samples with yellow, blue, and red iron oxide. The sample with red and black iron oxides, and the sample with yellow, blue, red, and black iron oxides blocked ultraviolet through to near-infrared. It can be concluded that dark colored iron oxide combinations are effective at blocking from ultraviolet through to visible light and near-infrared radiation. The results of this study may also suggest that biological colour of human skin and subcutaneous tissues are conserved for comprehensive photoprotection.

High efficiency and high transmission asymmetric polarization converter with chiral metasurface in visible and near-infrared region

Polarization manipulation of light is of great importance because it could promote development of wireless communications,biosensing,and polarization imaging.In order to use natural light more efficiently,it is highly demanded to design and fabricate high performance asymmetric polarization converters which could covert the natural light to one particular linearly polarized light with high efficiency.Traditionally,polarizers could be achieved by controllers with crystals and polymers exhibiting birefringence.However,the polarizers are bulky in size and the theoretical conversion efficiency of the polarizers is limited to 0.5 with unpolarized light incidence.In this paper,we propose a polarization converter which could preserve high transmission for one linearly polarized light and convert the orthogonal linearly polarized light to its cross-polarized with high transmittance based on a multi-layer chiral metasurface.Theoretical results show that normally incident y-polarized light preserves high transmittance for the wavelength range from 685 nm to 800 nm while the orthogonal normally incident x-polarized light is efficiently converted to the y-polarized light with high transmittance from 725 nm to 748 nm.Accordingly,for unpolarized light incidence,transmittance larger than 0.5 has been successfully achieved in a broadband wavelength range from 712 nm to 773 nm with a maximum transmittance of 0.58 at 732 nm.

A Visible Light Imaging System for the Estimation of Plasma Vertical Displacement in J-TEXT

A wide-viewing-angle visible light imaging system （VLIS） was mounted on the Joint Texas Experimental Tokamak （J-TEXT） to monitor the discharge process. It is proposed that by using the film data recorded the plasma vertical displacement can be estimated. In this paper installation and operation of the VLIS are presented in detailed. The estimated result is further compared with that measured by using an array of magnetic pickup coils. Their consistency verifies that the estimation of the plasma vertical displacement in J-TEXT by using the imaging data is promising.

Biological Defenses against Ultra-Violet, Visible Light, and Near-Infrared Exposure

Objective: Humans are increasingly exposed to artificial light and electromagnetic wave radiation, in addition to solar radiation. Many studies have shown the biological effects of ultra-violet and near-infrared exposure, but few have extensively investigated the innate biological defenses within human tissues against visible light and near-infrared exposure. Herein, we investigated spectral properties of endogenous human biological defenses against ultra-violet to near-infrared. Methods: A double-beam spectrophotometer (190 - 2700 nm) was used to measure the transmission spectra of a saline solution used to imitate perspiration, and oil to imitate sebum, as well as human skin, blood, adipose tissue, and muscle. Results: Saline (thickness, 0.5 mm) blocked 27.5% - 98.6% of ultra-violet, 13.2% - 34.3% of visible light, and 10.7% - 99.8% of near-infrared. Oil (thickness, 0.5 mm) blocked 50.5% - 100% of ultra-violet, 28.7% - 54.8% of visible light, and 19.0% - 98.3% of near-infrared. Blood thicknesses of 0.05 and 0.5 mm blocked over 97.8%, 100% of ultra-violet, over 94.6%, 99.7% of visible light, and over 75.8%, 99.4% of near-infrared, respectively. Skin thicknesses of 0.25 and 0.5 mm blocked over 99.4%, 100% of ultra-violet and over 94.3%, 99.7% of visible light, and over 74.7%, 93.5% of near-infrared, respectively. Adipose tissue thickness of 0.25 and0.5 mm blocked over 98.3%, 100% of ultra-violet, over 94.7%, 99.7% of visible light, and over 88.1%, 98.6% of near-infrared, respectively. Muscle thickness of 0.25 and0.5 mm blocked over 95.4%, 99.8% of ultra-violet, over 93.1%, 99.5% of visible light, and over 86.9%, 98.3% of near-infrared, respectively. Conclusions: Humans possess endogenous biological protection against ultra-violet, visible light and near-infrared exposure on multiple levels, including through perspiration, sebum, blood, skin, adipose tissue, and muscle. Since solar and artificial radiation affects human tissues, biological defenses made of biological materials may be induced to protect subcutaneous tissues against these wavelengths.

Intelligent MRI Room Design Using Visible Light Communication with Range Augmentation

Radio waves and strong magneticfields are used by Magnetic Reso-nance Imaging(MRI)scanners to detect tumours,wounds and visualize detailed images of the human body.Wi-Fi and other medical devices placed in the MRI procedure room produces RF noise in MRI Images.The RF noise is the result of electromagnetic emissions produced by Wi-Fi and other medical devices that interfere with the operation of the MRI scanner.Existing techniques for RF noise mitigation involve RF shielding techniques which induce eddy currents that affect the MRI image quality.RF shielding techniques are complex and lead to RF leak-age.VLC(Visible light Communication)is an emerging and efficient technology to avoid RF interference near MRI scanners.Range augmentation with power conservation of the LED is a big challenge in existing VLC systems.The major objective of the proposed work is to develop an intelligent-MRI room design without RF interference using visible light communication and enhance the distance between VLC transmitter and VLC receiver.In this paper,it is proposed to implement VLC using On-Off keying modulation and enhance distance using large active area photodiodes with Automatic Gain Control Circuit(AGC)using software and hardware.The performance of the proposed intelligent MRI-VLC system is analyzed by calculating Bit Error Rate at an inclined distance of 50 cm away from line of sight of the LED.The Experimental results showed that the maximum distance achieved was 400 cm at Bit Error Rate(BER)of 1.5×10^(-5).

FY-3D Sent Back First Visible Light Images

China successfully launched FY-3D by a LM-4C carrier rocket from the Taiyuan Satellite Launch Center at 02：35 Beijing time on November 15.The mission also carried the HEAD-1experiment satellite which was developed by SAST.The LM-4C carrier rocket was developed by SAST.22 technological improvements were made for this launch mission to meet the satellite’s requirement and improve the flight reliability.So far,

The Research of Indoor Positioning Based on Visible Light Communication

The key techniques in indoor positioning based on visible light communication and the state of the art of this research were surveyed. First, the significance of indoor positioning based on visible light communication from two aspects of the limitations of current indoor positioning technology and the advantages of visible light communication was discussed; And then, the main four technology of indoor positioning based on visible light communication were summarized and the triangulation of RSS method and the principle of image positioning were introduced in detail; Next, the performance characteristics of various typical algorithms were compared and analyzed; In the end, several suggestions on future research of indoor positioning based on visible light communication were given.

Research on the detection of early caries based on hyperspectral imaging

Objective:We applied hyperspectral imaging(HSI)system to distinguish early caries from soundand pigmented areas.It will provide a theoretical basis and technical support,for research anddevelopment of an instrument that could be used for screening and detection of early dentalcaries.Methods:Eighteen extracted human teeth(molars and premolars),with varying degrees ofnatural pathology and no degree of decay involving dentin were obtained.HSI system with awavelength range from 400 to 1000nm was used to obtain images of all 18 teeth containingsound,carious and pigmented areas.We compared the spectra of the wavebands at both 500 nmand 780 nm from the different tooth states,and the reflectance diference bet ween sound versuscarious lesions and sound versus pigmented areas,respectively.Results:There was a slight diference in refectance bet ween carious areas and pigmented areas at500 nm.A substantial difference was additionally noted in refectance bet ween carious areas andpigmented areas at 780 nm.Conclusion:The results have shown that the interference of tooth surface pigment can be elim-inated in the near-infrared(NIR)waveband,and the caries can be effectively identifed from the pigmented areas.Thus,it could be used to detect carious areas of teeth in place of the traditionalvisual inspection method or white light endoscopy.Clinical significance:The NIR difused light signal enables the identification of early caries frompigment and other interference,providing a reasonable detection tool for early detection andearly treatment of teeth diseases.

Intelligent Fusion of Infrared and Visible Image Data Based on Convolutional Sparse Representation and Improved Pulse-Coupled Neural Network

Multi-source information can be obtained through the fusion of infrared images and visible light images,which have the characteristics of complementary information.However,the existing acquisition methods of fusion images have disadvantages such as blurred edges,low contrast,and loss of details.Based on convolution sparse representation and improved pulse-coupled neural network this paper proposes an image fusion algorithm that decompose the source images into high-frequency and low-frequency subbands by non-subsampled Shearlet Transform(NSST).Furthermore,the low-frequency subbands were fused by convolutional sparse representation(CSR),and the high-frequency subbands were fused by an improved pulse coupled neural network(IPCNN)algorithm,which can effectively solve the problem of difficulty in setting parameters of the traditional PCNN algorithm,improving the performance of sparse representation with details injection.The result reveals that the proposed method in this paper has more advantages than the existing mainstream fusion algorithms in terms of visual effects and objective indicators.

Fabrication of PdSe2/GaAs Heterojunction for Sensitive Near-Infrared Photovoltaic Detector and Image Sensor Application

In this study,we have developed a high-sensitivity,near-infrared photodetector based on PdSe2/GaAs heterojunction,which was made by transferring a multilayered PdSe2 film onto a planar GaAs.The as-fabricated PdSe2/GaAs heterojunction device exhibited obvious photovoltaic behavior to 808 nm illumination,indicating that the near-infrared photodetector can be used as a self-driven device without external power supply.Further device analysis showed that the hybrid heterojunction exhibited a high on/off ratio of 1.16×10^5 measured at 808 nm under zero bias voltage.The responsivity and specific detectivity of photodetector were estimated to be 171.34 mA/W and 2.36×10^11 Jones,respectively.Moreover,the device showed excellent stability and reliable repeatability.After 2 months,the photoelectric characteristics of the near-infrared photodetector hardly degrade in air,attributable to the good stability of the PdSe2.Finally,the PdSe2/GaAs-based heterojunction device can also function as a near-infrared light sensor.

Multiscale method for identifying and marking the multiform fractures from visible-light rock-mass images

Multiform fractures have a direct impact on the mechanical performance of rock masses.To accurately identify multiform fractures,the distribution patterns of grayscale and the differential features of fractures in their neighborhoods are summarized.Based on this,a multiscale processing algorithm is proposed.The multiscale process is as follows.On the neighborhood of pixels,a grayscale continuous function is constructed using bilinear interpolation,the smoothing of the grayscale function is realized by Gaussian local filtering,and the grayscale gradient and Hessian matrix are calculated with high accuracy.On small-scale blocks,the pixels are classified by adaptively setting the grayscale threshold to identify potential line segments and mini-fillings.On the global image,potential line segments and mini-fillings are spliced together by progressing the block frontier layer-by-layer to identify and mark multiform fractures.The accuracy of identifying multiform fractures is improved by constructing a grayscale continuous function and adaptively setting the grayscale thresholds on small-scale blocks.And the layer-by-layer splicing algorithm is performed only on the domain of the 2-layer small-scale blocks,reducing the complexity.By using rock mass images with different fracture types as examples,the identification results show that the proposed algorithm can accurately identify the multiform fractures,which lays the foundation for calculating the mechanical parameters of rock masses.

Visibility enhancement in two-dimensional lensless ghost imaging with true thermal light

We report an experimental demonstration of two-dimensional（2D） lensless ghost imaging with true thermal light. An electrodeless discharge lamp with a higher light intensity than the hollow cathode lamp used before is employed as a light source. The main problem encountered by the 2D lensless ghost imaging with true thermal light is that its coherence time is much shorter than the resolution time of the detection system. To overcome this difficulty we derive a method based on the relationship between the true and measured values of the second-order optical intensity correlation, by which means the visibility of the ghost image can be dramatically enhanced. This method would also be suitable for ghost imaging with natural sunlight.

Ghost Imaging with High Visibility Using Classical Light Source

We experimentally demonstrate a novel ghost imaging experiment utilizing a classical light source, capable of resolving objects with a high visibility. The experimental results show that our scheme can indeed realize ghost imaging with high visibility for a relatively complicated object composed of three near-ellipse-shaped holes with different dimensions. In our experiment, the largest hole is -36 times of the smMlest one in area. Each of the three holes exhibits high-visibility in excess of 80%. The high visibility and high spatial-resolution advantages of this technique could have applications in remote sensing.

Modeling for mung bean variety classification using visible and near-infrared hyperspectral imaging

This study was carried out to investigate the feasibility of using visible and near infrared hyperspectral imaging for the variety classification of mung beans.Raw hyperspectral images of mung beans were acquired in the wavelengths of 380-1023 nm,and all images were calibrated by the white and dark reference images.The spectral reflectance values were extracted from the region of interest(ROI)of each calibrated hyperspectral image,and then they were treated as the independent variables.The dependent variables of four varieties of mung beans were set as 1,2,3 and 4,respectively.The extreme learning machine(ELM)model was established using full spectral wavelengths for classification.Modified gram-schmidt(MGS)method was used to identify effective wavelengths.Based on the selected wavelengths,the ELM and linear discriminant analysis(LDA)models were built.All models performed excellently with the correct classification rates(CCRs)covering 99.17%-99.58% in the training sets and 99.17%-100%in the testing sets.Fifteen wavelengths(432 nm,455 nm,468 nm,560 nm,705 nm,736 nm,760 nm,841 nm,861 nm,921 nm,930 nm,937 nm,938 nm,959 nm and 965 nm)were recommended by MGS.The results demonstrated that hyperspectral imaging could be used as a non-destructive method to classify mung bean varieties,and MGS was an effective wavelength selection method.

INTRINSIC OPTICAL SIGNAL IMAGING OF RETINAL ACTIVITY IN FROG EYE

Using a near-infrared(NIR)light flood-illumination imager equipped with a high-speed(120 Hz)CCD camera,we demonstrated optical imaging of stimulus-evoked retinal activity in isolated,but intact,frog eye.Both fast and slow transient intrinsic optical signals(IOSs)were observed.Fast optical response occurred immediately after the stimulus onset,could reach peak magnitude within 100 ms,and correlated tightly with ON and OFF edges of the visible light stimulus;while slow optical response lasted a relatively long time(many seconds).High-resolution images revealed both positive(increasing)and negative(decreasing)IOSs,and dynamic optical change at individual CCD pixels could often exceed 10%of the background light intensity.Our experiment on isolated eye suggests that further development of fast,high(sub-cellular)resolution fundus imager will allow robust detection of fast IOSs in vivo,and thus allow noninvasive,three-dimensional evaluation of retinal neural function.

Hyperspectral Images-Based Crop Classification Scheme for Agricultural Remote Sensing

Hyperspectral imaging is gaining a significant role in agricultural remote sensing applications.Its data unit is the hyperspectral cube which holds spatial information in two dimensions while spectral band information of each pixel in the third dimension.The classification accuracy of hyperspectral images(HSI)increases significantly by employing both spatial and spectral features.For this work,the data was acquired using an airborne hyperspectral imager system which collected HSI in the visible and near-infrared(VNIR)range of 400 to 1000 nm wavelength within 180 spectral bands.The dataset is collected for nine different crops on agricultural land with a spectral resolution of 3.3 nm wavelength for each pixel.The data was cleaned from geometric distortions and stored with the class labels and annotations of global localization using the inertial navigation system.In this study,a unique pixel-based approach was designed to improve the crops'classification accuracy by using the edge-preserving features(EPF)and principal component analysis(PCA)in conjunction.The preliminary processing generated the high-dimensional EPF stack by applying the edge-preserving filters on acquired HSI.In the second step,this high dimensional stack was treated with the PCA for dimensionality reduction without losing significant spectral information.The resultant feature space(PCA-EPF)demonstrated enhanced class separability for improved crop classification with reduced dimensionality and computational cost.The support vector machines classifier was employed for multiclass classification of target crops using PCA-EPF.The classification performance evaluation was measured in terms of individual class accuracy,overall accuracy,average accuracy,and Cohen kappa factor.The proposed scheme achieved greater than 90%results for all the performance evaluation metrics.The PCA-EPF proved to be an effective attribute for crop classification using hyperspectral imaging in the VNIR range.The proposed scheme is well-suited for practical applications of crops and landfill estimations using agricultural remote sensing methods.