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.

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.

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.

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 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.

Transmittance Spectrum of Unbranded Sunglasses Using Spectrophotometer

Background: The sunglass standards are not strictly implemented in many countries except Aus-tralia. The purpose of the study was to evaluate the optical properties of unbranded sunglasses for light transmittance. Methods: Unbranded sunglasses with no information about their specifications were included. They were allocated to two groups based on their prices;the ones > 25 US$ (Group A) and the cheaper ones (Group B). Their transmittance spectrum was measured between 190 nm and 900 nm using a double beam scanning spectrophotometer. The European standard for sunglasses was used to evaluate their compliance regarding ultraviolet radiation (UVR) transmittance and minimum requirement for wearing when driving. Results: Thirty-eight sunglasses (Group A = 20 and Group B = 18) were evaluated. Four sunglasses in each group were non-compliant. Percentage transmittance of visible light was <8% in five sunglasses of Group A and in three of Group B, so these were not appropriate to wear when driving. Totally six sunglasses of Group A and five of Group B were non-compliant and/or inappropriate to wear when driving. Conclusions: Based on our findings about their UVR protection and visible light transmittance %, eye care professionals must warn people against the use of unbranded sunglasses without any information about their specifications.

Physical Properties of Water under the Actionby Electricity and Light

The significance of research of water system is demonstrated by the experiments and statistical data. Some physical and chemical properties of water system affected by various factors in the nature are given. It also points out that further research of the effect on extremely complicated water system caused by electricity, magnetic field, sound and light now becomes an important research subject.

基于自编码器的红外与可见光图像融合算法

针对目前红外与可见光图像融合过程中,图像特征提取不充分、中间层信息丢失以及融合图像细节不够清晰的问题,提出了一种基于自编码器的端到端图像融合网络结构。该网络由编码器、融合网络和解码器3部分组成。将高效通道注意力机制和混合注意力机制引入到编码器和融合网络中,利用卷积残差网络(convolutional residual network,CRN)基本块来提取并融合红外图像和可见光图像的基本特征,然后将融合后的特征图输入到解码器进行解码,重建出融合图像。选取目前具有典型代表性的5种方法在主客观方面进行对比。在客观方面,较第2名平均梯度、空间频率和视觉保真度分别提升了21%、10.2%、7.2%。在主观方面,融合后的图像目标清晰、细节突出、轮廓明显,符合人类视觉感受。

基于特征相似性的红外与可见光图像融合方法

单一图像无法全面描述目标的信息,实际应用价值低,针对当前红外与可见光图像融合方法存在的一些不足,如:融合质量差等,为了获得更加理想的红外与可见光图像融合效果,提出了基于特征相似性的红外与可见光图像融合方法。首先分析当前红外与可见光图像融合的研究进展,指出各种方法的局限性,然后采用红外图像和可见光图像,并对它们进行图像去噪、增强处理,采用卷积神经网络提取红外与可见光图像的特征,最后根据特征相似性进行红外与可见光图像融合,并对红外与可见光图像融合效果进行了测试,结果表明,本方法提升了红外与可见光图像融合质量,融合效果要明显优于其他红外与可见光图像融合方法。

深度学习与图像融合的行人检测算法研究

为解决智能辅助驾驶技术中可见光摄像机受光照和气候影响而导致行人目标识别困难的问题。通过研究图像融合技术,结合深度卷积神经网络,实现并改进了一种道路行人目标检测算法。方法是利用多源传感器图像融合技术,采用可见光相机与红外热成像相机融合的策略,以Faster RCNN算法为基础,从改进网络结构、特征融合、优化模型训练等方面展开研究,对复杂环境下的行人检测与定位跟踪展开研究,提出一种基于图像融合技术和改进的深度卷积神经网络的道路行人目标检测算法。实验结果表明,该算法对复杂气候环境下行人目标检测提高了检测效率和准确率,增加了智能辅助驾驶汽车的安全性。

开展可见光—红外线—太赫兹波成像系列实验培养解决真实问题人才

物理学的研究成果有力推动了三次工业革命的发展。进入新世纪以来,量子计算、低维物理、量子探测等现代物理研究成果正在促进第四次工业革命暨工业4.0向纵深发展。笔者在大学物理实验中规划布局多层次物理实验题目,以开展可见光-红外线-太赫兹波探测与成像系列实验为例,介绍了学生深刻理解不同波段的电磁波在新旧产业领域应用性的异同。这一教学模式有利于学生掌握近现代物理成果与实验综合技能,培养他们成为解决新产业领域面临的真实问题的新理工科人才,从容面对新技术革命与职业选择。

基于鞍山式铁矿成像光谱的融合算法研究

铁矿资源是我国经济发展和社会进步的物质基础。在铁矿开采过程中,快速精准地确定铁矿品位,对矿山开采决策及经济效益具有重要影响。高光谱成像技术具有影像覆盖范围广、精度高等优势,已广泛应用于矿石分类及成分反演等领域。然而目前高光谱成像传感器的波段范围主要为可见短近红外(Vis-SWIR)和近红外(NIR)两类,且两类数据多为独立获取,缺乏连续性,采用单一数据所建模型的精度往往偏低。因此融合多传感器所获光谱数据,可有效解决单一传感器波段范围小、包含目标特征波段少等问题,提高基于高光谱成像技术的铁矿品位反演精度。使用Pika L与Pika NIR-320高光谱成像仪,分别在Vis-SWIR与NIR两个波段范围内采集鞍山式铁矿的成像光谱数据,提出了基于互信息(MI)的光谱串联融合方法,该方法首先对两组光谱数据进行预处理,然后对处理后的数据进行互信息计算以此对光谱数据进行串联融合。最后分别以Vis-SWIR、NIR以及基于不同波段串联融合的光谱数据为数据源,建立RBF神经网络品位反演模型,并以融合前后光谱数据所建模型的准确性与精度为融合算法有效性的判别指标。结果表明,光谱数据串联融合后所建模型的准确性与精度高于单独使用Vis-SWIR、NIR光谱数据所建模型的准确性与精度。与基于其余波段串联融合的光谱数据相比,在基于互信息计算得出的959.89nm处串联融合后光谱数据所建模型的准确性与精度最高,R2为0.88,RPD为2.97,RMSE为4.464,MAE为3.32。该研究针对多传感器光谱融合提出了一种新思路,对成像光谱技术应用于铁矿品位反演具有现实指导意义。

不同离子掺杂策略下的无铅卤化物钙钛矿发光性质及其应用

综述不同离子掺杂策略下无铅卤化物钙钛矿于可见及近红外区域的发光性质及其应用研究进展。无铅卤化物钙钛矿因其独特的光学性质在照明、显示、防伪和生物成像等技术领域有着广泛的应用。针对荧光材料发光性能进行调控,有利于拓展其在温度传感、防伪识别、静脉成像等技术领域的应用。普通的无铅卤化物钙钛矿自身发光效率低且发光性质单一,限制了其实际应用。为解决这一问题,研究人员采用不同离子掺杂策略以实现针对可见及近红外区域的发光调控,拓展无铅卤化物钙钛矿的应用场景。随着无铅卤化物钙钛矿在可见及近红外光领域的广泛应用,具有高效荧光量子产率的荧光材料被不断研发出来,但现阶段的报道大多仅集中在发光效率的研究上。当前的研究工作还应侧重于对发光热∕水稳定性、合成原料价格及合成工艺复杂性的改善,以进一步挖掘高效发光材料的商用价值。

基于可见/近红外光谱与化学计量学的杏品种无损鉴别方法

新疆南疆是全国杏种植面积最大的地区,杏品种繁多。在杏果品市场中,不同品种杏的品质和价格差异较大,以次充好、品质参差不齐等现象严重制约了新疆杏果业的发展。为探究利用可见/近红外光谱快速检测杏品种的可行性,基于样品的可见/近红外光谱与化学计量学方法,对新疆南疆地区的6个品种杏进行定性判别分析,建立一种杏品种的无损鉴别方法。采用光谱仪采集6个品种杏(“黄杏”、“橄榄杏”、“小白杏”、“小米杏”、“库买提杏”、“小吊干杏”)在350~1 000 nm(VIS/NIR)和1 000~2 500 nm(NIR)两个范围内的光谱数据,去除原始光谱首端的噪声后,对保留的光谱使用Savitzky-Golay(SG)卷积平滑和多元散射校正(MSC)处理以消除光谱存在的干扰信息,采用主成分分析(PCA)、竞争性自适应重加权算法(CARS)、随机蛙跳(RF)、连续投影算法(SPA)对原始光谱降维,结合线性判别法(LDA)、朴素贝叶斯(NB)、 K最近邻(KNN)和支持向量机(SVM)对全光谱和降维后光谱建模对比。结果表明:基于全光谱数据建立的模型有较为准确的分类结果,在VIS/NIR范围,SVM模型分类正确率为95.7%, NIR范围内,LDA模型分类正确率为97.8%;采用PCA、 CARS-SPA、 RF-SPA与SPA方法对光谱数据降维后,模型仍能保持较高的分类精度,在VIS/NIR范围,PCA-LDA模型的分类正确率为97.8%, NIR范围内,RF-SPA-LDA模型的分类正确率高达95.7%。不同模型的结果表明,VIS/NIR范围内的模型分类效果优于NIR范围内模型;4种降维方法中,PCA方法降维效果最优;4种分类器中,LDA与SVM模型的正确率高于NB与KNN模型,更适用于杏品种的鉴别。结果表明,基于VIS/NIR范围光谱结合主成分分析和线性判别法可以实现杏品种的快速无损鉴别,为杏果实的在线分拣鉴定提供了新途径。

Lanthanide complexes-functionalized ordered mesoporous TiO_2:Multicolor emission(visible and near-infrared luminescence) based on visible-light sensitization

Recently,much attention has been paid to the lanthanide luminescent materials based on the visiblelight sensitization for their potential applications in the fields of bio-imaging and optical devices.In this work,the lanthanide complexes have been covalently bonded to the ordered mesoporous titania（OMT） matrix,and the resulting titania-based hybrid ordered mesoporous materials（named as LnDBOMT,Ln = Eu,Sm,Yb,Nd） were characterized by using Fourier-transform infrared（FT-IR） spectroscopy,small-angle X-ray powder diffraction（SAXD）,N2 adsorption-desorption isotherms,transmission electron microscopy（TEM）,fluorescence spectroscopy,and thermogravimetric analysis.Generally,exciting with visible light is advantageous over UV excitation.Of importance here is that,under excitation with visible light,the LnDB-OMT all show characteristic visible（Eu3＋,Sm3＋） as well as nearinfrared（Sm3＋,Yb3＋,Nd3＋） luminescence of the corresponding Ln3＋ ions（multicolor emission covered from 500 to 1400 nm spectral region）,which is attributed to the energy transfer from the ligands to the Ln3＋ ions via an antenna effect.

基于深度学习的红外图像超分辨率重建方法

为了提高红外图像的超分辨率重建效果,提出基于深度学习的红外图像超分辨率重建方法。利用红外图像的反射特性与红外辐射特性建立红外图像的显著性区域检测模型;通过可见光与近红外图像之间样貌差异度水平检测图像的边缘轮廓特征,提取可见光与近红外光融合性特征参数;根据融合层次不同对图像信号级、像素级、特征级、决策级四个维度进行重建,提取图像的边缘、形状、纹理特征;根据特征分布的噪声水平与配准质量,采用深度学习算法实现对红外图像超分辨率重建。仿真测试结果得出,该方法进行红外图像重建的显著性特征检测能力较强,重建后将图像分辨率提升到1280×960 PPI,模板匹配准确率为49.4%,峰值信噪比PSNR值高于36.34 dB,结构相似度SSIM值高于0.972,重建效果较好,更适合用于特定场景下的红外图像目标特征识别。

红外与可见光双模导引头光学系统设计

为了提升导弹在复杂环境下的寻的制导能力,设计了一种红外与可见光双模式导引头光学系统。该方案中采用分光镜透射红外光反射可见光,使结构布局更加紧凑,实现红外与可见光共口径,同时配合红外材料选取,实现光学被动消热差设计。中红外模式视场角3°×2.3°,可见光模式视场角5°×4°,工作温度20℃条件下,双模式在截止频率处,MTF(Modulation Transfer Function)值均大于0.4。红外与可见光双模式光学系统适合应用于复杂环境的导弹制导,对温度有良好的适应性,具有较好的成像质量,满足系统的性能要求。

基于可见光与红外图像的弱光条件下目标检测

图像融合是将多个输入图像合并成一个单一图像的技术。可见光红外图像融合能提高目标检测的准确性,但在低光照场景下往往效果不佳。基于此,提出一种新的融合模型DAPR-Net。该模型具有跨层残差连接的编解码结构,将编码器的输出与解码器的对应层的输入相连接,加强各层卷积层间的信息传递。在编码器中设计了双注意力特征提取模块AFEM,使得网络能够更好地区分融合图像与输入的可见光和红外图像之间的差异,同时保留两者的关键信息。在多个公开数据集上与6种先进方法进行对比,实验结果表明,与基准PIAFusion模型相比,该模型在LLVIP和MSRS数据集上的信息熵、空间频率、平均梯度、标准差、视觉保真度指标分别提高了0.849、3.252、7.634、10.38、0.293和2.105、2.23、4.099、27.938、0.343;在YOLOV5目标检测网络上,LLVIP和MSRS数据集的平均精度均值、召回率、精确率、F1值指标分别提高了8.8、1.4、1.9、1.5个百分点和7.5、1.4、8.8、1.2个百分点,相较于其他融合方法表现出更显著的优势。