576 results about "Night vision" patented technology

Disclosed is a nighttime unmanned aerial vehicle (UAV) object tracking method fusing a hybrid attention mechanism. According to the method, a night vision image enhancement model is employed to enhance various nighttime image frames in a night vision video sequence of UAV before performing image object tracking and recognition, to improve the accuracy of object tracking for nighttime images. With the aid of a spatial channel hybrid attention mechanism, the night vision image enhancement model can adaptively learn spatial channel features, enhancing generalization ability, and enabling the network model to focus on more effective features. Additionally, a denoising processing module is introduced to remove noise hidden in the nighttime images, improving the object positioning accuracy and tracking performance of UAV in nighttime scenarios, and reducing the failure probability of object tracking by UAV in nighttime scenarios.

The invention relates to the technical field of image processing, in particular to a low-light and infrared image fused night vision imaging method and system. According to the method, multi-source data collaboration is realized by constructing a dual-band polarization feature cube, a degradation rule of fog scattering on low-light texture is accurately quantified, and a scattering invariance enhanced image is generated; based on fog concentration gradient dynamic partitioning, low-light details and infrared contours are fused in a low-concentration area, polarization state penetrating dense fog is recombined in a high-concentration area, finally, a night vision image with high definition, high scattering resistance and scene adaptability is output, and the identification capacity and monitoring reliability of fog night road targets are improved.

The invention relates to the technical field of wireless communication, in particular to an intelligent wireless communication control method applied to ships and boats. The method comprises the following steps: acquiring radar original point cloud data, an AIS ship attribute data set, a Beidou navigation state data set and night vision target feature data through a multi-dimensional sensor, and constructing ship multi-source standardized preprocessing data; therefore, the functions of multi-source heterogeneous data fusion, dynamic channel adaptive modulation, distributed relay communication guarantee, real-time air route dynamic planning, intelligent instruction generation and the like are realized; the problems of high data isolation, large transmission delay, rigid navigation path, slow obstacle avoidance response, insufficient formation collaboration and the like in the existing ship communication control technology are solved, and the communication stability, the navigation safety and the overall combat effectiveness of the ship formation in a complex dynamic environment are remarkably improved.

An XR system is disclosed having a night mode to optimize performance in low light conditions. The system estimates a user's dark adaptation level based on captured image data and selects a rendering configuration aligned with the user's vision. For example, spatial resolution, temporal resolution, color mode, and brightness are adjusted based on whether the adaptation level is scotopic, mesopic, or photopic. With eye tracking, foveated rendering is used for cones and periphery rendering for rods. Without eye tracking, modes with different wavelengths and colorization are employed. The night mode aims to maximize information visible on the display, conserve power by only showing what eyes can perceive, and preserve night vision by avoiding over-stimulating rods.

The invention relates to the technical field of intelligent night vision light source construction, and discloses an RGB intelligent night vision light source construction method and system, and the method comprises the steps: collecting the environment light intensity and other data of a light source construction region, obtaining environment perception data, constructing an environment feature tensor, and obtaining an initial control parameter through a dual-delay network; inquiring an LED array, configuring spatial light and pulse width, and obtaining a tunable composite spectrum by using initial parameter driving; a light reflection target is inquired, spectrum irradiation is used, data are collected, and an illumination-imaging joint optimization model is constructed through processing to obtain target data; target features are identified by using target data, a scene semantic vector and a light source control strategy are constructed, unit parameters are optimized through matrix calculation and decomposition, equipment is deployed to obtain a target LED array, and the RGB intelligent night vision light source is constructed. According to the invention, the accuracy of night vision imaging of the RGB intelligent night vision light source can be improved.

The invention relates to the technical field of luminescent materials, and discloses a preparation method and application of a transition metal and chalcogen ion doped metal halide high-efficiency wide-spectrum luminescent material, the chemical formula of the transition metal and chalcogen ion doped metal halide is Cs2Sn1-x-yCl6: x% Te < 4 + >, yMo < 4 + >, the ultra-wideband fluorescent powder converted light emitting diode (LED) covers the range from visible light (VIS) to near infrared light (NIR), and shows remarkable potential in practical application. According to the invention, ultra-wide spectrum emission from 400 nm to 1400 nm is realized in Mo < 4 + >-Te < 4 + > co-doped Cs2SnCl6, and the photoluminescence quantum yield of 95.3% is achieved, the excellent performance is realized through efficient energy transfer from Te < 4 + > to Mo < 4 + > and passivation synergistic effect of vacancy defects, and the performance can be verified through theoretical calculation and spectral research; finally, the ultra-wideband fluorescent powder conversion LED based on the Mo < 4 + > and Te < 4 + > co-doped Cs2SnCl6 is successfully prepared and is applied to the fields of blood gas analysis and night vision imaging.

The invention relates to a system and a method for making a colored low-light image. The system for making the color low-light-level image comprises a high-sensitivity CMOS imaging module which is used for enhancing the photon collection capability and reducing the noise level to complete imaging; the image enhancement processing module adopts a histogram equalization algorithm and comprises the steps of calculating a gray histogram of the original image, calculating a cumulative distribution function according to the gray histogram and performing gray mapping to obtain an enhanced gray value; the image noise reduction processing module is used for carrying out noise reduction on the image after enhancement processing, and filtering is carried out by adopting a night image noise reduction technology, a bilateral filtering method including spatial domain noise reduction and a band-pass filter including frequency domain noise reduction; and the colorful low-light-level image generation module obtains a colorful low-light-level night vision image by adopting an interpolation algorithm and makes a colorful low-light-level image. According to the system and the method for manufacturing the colored low-light-level image, special equipment is not depended on, the imaging quality of the colored low-light-level image can be improved, and the colored low-light-level image can be manufactured.

The invention discloses a radio frequency detection and identification method and device fusing low-light and thermal imaging, and relates to the technical field of detection and identification, and the method comprises the steps: obtaining the angle information of a radio frequency signal through an array antenna, and generating the preliminary spatial signal distribution of a target region; performing image alignment fusion by combining the low-light night vision image and the thermal imaging information to generate a preliminary fusion image; spatial signal distribution is mapped to a fused image coordinate, and a spatial corresponding relation between a radio frequency signal and an image is established; fusing the radio frequency signal features and the image features based on the corresponding relation to generate joint features; and target positioning and labeling are realized by using the combined features. The technical problem of low target identification and positioning precision in a complex environment in the prior art is solved, and the technical effect of improving the target identification and positioning precision is achieved through more comprehensive information acquisition and data fusion.

An ophthalmic lens configured to correct and / or treat at least one condition of the eye (e.g., presbyopia, myopia, hyperopia, astigmatism, binocular vision disorders, night vision image quality, and / or visual fatigue syndrome) comprising: a base power profile; and at least one pulse selected to modify the base power profile.

The invention discloses a laser point cloud and image fused power transmission channel external damage hidden space distance measuring device and a starting method thereof.The power transmission line external damage hidden danger monitoring device is installed on a power transmission tower and mainly comprises a laser point cloud acquisition module, a common light image acquisition module and a night vision image acquisition module; according to the external damage hidden danger space distance measuring device, a laser point cloud acquisition module and an image acquisition module are integrated into the device, and a direction adjusting mechanism is arranged at the installation position of the laser point cloud acquisition module and the image acquisition module; the method comprises the steps of starting point cloud data acquisition to reconstruct point cloud data and starting a distance measurement method. According to the method, the visualization function of an existing power transmission line can be considered, the distance from the external damage hidden danger to the power transmission body can be calculated, quantitative analysis of the external damage hidden danger is achieved, and invalid warning of the external damage hidden danger is greatly reduced.

The invention discloses infrared night vision AR (Augmented Reality) intelligent glasses based on multispectral fusion, and relates to the technical field of infrared intelligent application. High-precision scene perception in a low-light / light-free environment is realized by fusing dual-channel data of low-light imaging and infrared thermal imaging and combining cross-modal feature matching and dynamic pose compensation; an environment detail structure is restored by a low-light image enhancement technology, thermal feature targets such as organisms are accurately recognized through thermal imaging target segmentation, and a three-dimensional environment model with space geometric information and target attributes is constructed through heterogeneous feature fusion; and dynamically adjusting the display transparency of the key target in the AR view field through a virtual information layer adaptive mixing mechanism driven by a hot target attribute, and finally outputting a virtual-real fused enhanced view, thereby breaking through the illumination limitation of the traditional AR glasses, and improving the visual effect of the AR glasses. And immersive augmented reality experience with panoramic detail perception and hot target accurate positioning is provided for the user in a dark environment.

The invention discloses a nano-pillar array NaKSb photoelectric cathode for enhancing light absorption, which is characterized in that through the design of a double-layer TiOtwo-dimensional nano grating and a nano-pillar array structured NaKSb photoelectric cathode layer, the optical path of light with the wave band of 450-900 nm in the photoelectric cathode is increased under the condition that the thickness of the NaKSb photoelectric cathode is not increased, the reflectivity of the wave band of 400-600 nm is reduced, and the light absorption of the NaKSb photoelectric cathode is enhanced. The absorption rate at 400-1000 nm is improved by 32.28% compared with that of a traditional planar film type photoelectric cathode, the absorption rate at 800-1000 nm near-infrared band is improved by 40.27% compared with that of the traditional planar film type photoelectric cathode, the problem that the absorption of the traditional planar film type photoelectric cathode near-infrared band is insufficient is solved, and the photoelectric cathode is suitable for high-performance low-light night vision imaging devices.

The invention provides a low-power-consumption wireless camera self-adaptive night vision system and an energy-saving control method, and relates to the technical field of image communication and monitoring, an infrared detection unit is used for identifying human infrared signals so as to judge whether video recording needs to be started or not, a partition acquisition strategy is started according to personnel position coordinates, and meanwhile, the energy-saving control method is used for monitoring the human infrared signals. By concentrating night light supplement of the wireless camera and reducing misjudgment of moving objects such as animals, the endurance of the wireless camera is improved, and meanwhile useful video data are collected in a targeted mode, so that loss of personnel and property under the condition similar to camping is reduced.

The housing assembly of the panning binocular night vision system is configured to facilitate the night-vision monoculars being horizontally rotated outwards, thereby facilitating an expanded horizontal field of view. An example housing assembly comprises a bridge member, a first arm assembly and a second arm assembly rotatably coupled to a first end and a second end, respectively, of the bridge member, and a first pod and a second pod attached to a distal end of the first arm assembly and the second arm assembly, respectively. The first pod and the second pod serve as a housing for a first optical device and a second optical device, respectively. The first arm assembly and the second arm assembly each include a rotational connector, a pod adapter, and a mounting bracket used to pivotally couple the pod adapter to the rotational connector. The pod adapter and the mounting bracket of both the first arm assembly and the second arm assembly are configured to horizontally articulate and thereby facilitate rotating the first pod and the second pod, respectively, between a center-neutral position and a wide-angle position.

A method comprises illuminating an area using an infrared light source. The method further comprises, while the area is illuminated using the infrared light source, capturing one or more images of the area. The method further comprises analyzing the one or more images to identify an object in the area. The method further comprises, after identifying the object, illuminating the area using a visible light source.

A lighting system and assembly comprising a controller in operable communication with a light unit. The controller is configured to apply a lighting condition using the light unit for a target light color below an upper level of NVIS radiance while controlling a Melanopic-Photopic (M / P) ratio associated with the target light color, and also determine a color mixing for producing NVIS Green A light and NVIS white light for a plurality of levels of NVIS radiance which are less than a maximum NVIS radiance level for a set of M / P ratio values at an upper allowable limit and a set of M / P ratio values at a lower limit.

The invention discloses a scene-based non-uniformity correction method, and relates to the technical field of image processing. According to the method, the key frame and the non-key frame are identified by analyzing the difference degree of continuous image sequences of the night vision system, extracting the difference region and evaluating the importance score of the frame in combination with the information entropy of the image; for the key frame, carrying out full-frame storage and on-line average calculation to generate an initial non-uniformity correction parameter; non-key frames only reserve difference area data, local updating is carried out based on correction parameters of the key frames, and the correction effect is further optimized through statistical characteristics of difference areas; and the standard deviation convergence condition is dynamically adjusted, the non-uniformity correction precision is optimized, newly added key frames are automatically processed in the real-time image sequence, and redundant data are deleted. According to the method, the image processing efficiency and the correction precision are remarkably improved, the redundancy calculation and storage overhead are reduced, the adaptability is high, correction parameters can be optimized in real time, and the method is particularly suitable for efficient and accurate night vision system image processing.

A multi-accessory mount assembly for use with a firearm, and methods for coupling the assembly to the firearm are provided. The assembly may include a proximal portion having a lower surface configured to be removably coupled to the firearm and an upper surface configured to be removably coupled to a sub mount. The sub mount may be configured to be removably coupled to a first firearm accessory, e.g., an optic scope, a red dot sight, a reflex sight, a night vision monocular or scope, or a magnifier. The assembly further may include a distal portion extending distally from the proximal portion via a neck portion, such that the distal portion is elevated higher than the proximal portion. An upper surface of the distal portion may be configured to be removably coupled to a second firearm accessory, e.g., an infrared laser or a night vision monocular or scope.

The invention discloses an intelligent traffic multi-angle night vision snapshot camera device and system, and belongs to the technical field of image processing, and the device comprises a multi-mode sensing layer which is connected to a traffic information collection end; the anti-interference physical layer comprises a lens anti-interference module arranged at the traffic information acquisition end; the edge computing layer comprises an embedded NPU (Network Processing Unit) chip, and the chip realizes multi-stage distributed processing through a multi-stage processing mechanism; and the cloud collaboration layer realizes real-time synchronization and storage of data through a distributed server cluster in combination with a network communication module, and supports access of multiple terminal devices at the same time. In the implementation process of the technical scheme of the invention, multi-dimensional data acquisition is performed on a traffic scene through the multi-modal sensing layer, and distributed processing is performed on the acquired image through the edge calculation layer after acquisition is completed, so that multi-dimensional analysis of the traffic image is realized.

The invention relates to the technical field of luminescent materials, in particular to tungsten-doped double perovskite and a preparation method and application thereof. The first aspect of the invention is to provide tungsten-doped double perovskite, the chemical formula of the tungsten-doped double perovskite is Cs2Sn1-xCl6: xW < 4 + >, and x is greater than or equal to 0.1% and less than or equal to 5%. The invention further provides a preparation method of the tungsten-doped double perovskite, which comprises the following steps: mixing a Cs-containing compound, a Sn-containing compound, a W-containing compound and concentrated hydrochloric acid, heating, cooling, separating, washing and drying to obtain the tungsten-doped double perovskite. The third aspect of the invention is to provide application of the tungsten-doped double perovskite in the fields of near-infrared LEDs, night vision, safety monitoring or nondestructive analysis. The fourth aspect of the invention is to provide an optoelectronic device, and the luminescent material of the optoelectronic device adopts the tungsten-doped double perovskite.

The invention discloses a low-light image target detection method based on enhanced feature fusion, and belongs to the field of computer vision and target detection. According to the method, multilayer features are extracted by using a backbone network, a bidirectional multi-scale feature pyramid and three-path convolution fusion module is designed, shallow features and transverse jump connection are introduced in the fusion process, and efficient combination of spatial details and semantic information is realized; an intra-scale Transform encoder is adopted to enhance the feature expression ability, and in a decoding stage, a deformable attention and query selection strategy is combined, so that the detection efficiency and precision are improved; and end-to-end training is realized through Hungary matching and set loss. According to the invention, real-time high-precision target detection can be realized in a low-illumination environment, and the method is suitable for night vision monitoring and intelligent sensing scenes.

The invention discloses an intelligent inspection method and system based on night vision digital glasses. According to the method, a thermal infrared image, a visible light image, depth information and ambient light intensity data of an inspection area are collected in real time through night vision digital glasses. Feature level fusion is carried out on the infrared image and the visible light image by using an image fusion algorithm, depth information is corrected and optimized, and imaging parameters are automatically adjusted according to ambient light intensity data to ensure that the image is clear. Then, a deep learning algorithm is used to carry out real-time analysis on fused image data, a target is identified, and three-dimensional positioning and distance measurement are realized. And in combination with a preset risk model and a decision rule, the risk is evaluated, an acousto-optic early warning is sent to the inspection personnel through the glasses display module when an abnormality is found, and the risk information is transmitted to a remote monitoring center. In addition, inspection data are automatically recorded and an inspection report is generated. The method and the system effectively improve the inspection efficiency and accuracy, and are especially suitable for intelligent inspection tasks in complex environments.

The invention relates to the technical field of intelligent security and protection and intelligent old-age care monitoring, in particular to a collaborative tumble detection method based on Bayesian cognitive routing and spatio-temporal rhythm prior, which comprises the following steps: a dual-mode visual acquisition unit acquires a video stream; constructing a multi-mode tumble detection model, namely extracting video features, preliminary behavior probability distribution and statistical features from a video stream by utilizing a lightweight time sequence sensing network, calculating rhythm surprise by utilizing a neural state space rhythm model, calculating a routing activation probability by utilizing a Bayesian gating network and judging whether to intercept or not, if so, triggering the visual language large model; constructing a training mechanism of teacher-student alignment until the network converges; and outputting an identification result and executing a modal isolation data response strategy. The method has the beneficial effects that a'lightweight perception-large model rechecking 'bionic architecture is constructed, the detection precision is improved, the problems of infrared night vision and shielding are solved, false alarm and missing alarm caused by similar postures are reduced, and family privacy protection is also realized.

The invention provides a side slope deformation video monitoring method and system based on a night vision system, and relates to the technical field of geotechnical engineering safety monitoring. The method comprises the following steps: acquiring all-weather video stream data of a slope area to be monitored through a dual-mode night vision camera device, and preprocessing to obtain a slope deformation image; the slope deformation image is analyzed by adopting a digital image related technology to obtain a slope surface deformation condition, and the slope surface deformation amount is calculated to carry out multi-stage early warning; and inputting the slope surface deformation amount into the trained deformation trend prediction model based on the LSTM, and obtaining the predicted deformation amount for early warning. According to the invention, the bottleneck of night side slope on-line monitoring is broken through, 0.05 mm submillimeter level displacement measurement precision is realized through combination of the visible light-infrared dual-mode camera and the improved video image DIC flow analysis technology, the spatial-temporal feature fusion model is innovatively introduced to improve the early warning accuracy, and a reliable technical means is provided for side slope safety protection in a complex environment.

The invention discloses a high-definition night vision driving data enhancement method based on deep learning. The method comprises the following steps: S1, constructing a paired image sample set; s2, inputting the paired image sample set into a double-branch depth encoder network; s3, performing information interaction and fusion on the features extracted by the first branch and the second branch to obtain a fusion feature map; s4, performing target sensitivity modeling on the fused feature map, constructing a target sensitivity score map of an image region, and taking image block-level features as a search space; s5, introducing an improved badger algorithm to carry out adaptive optimization on the target sensitivity score map, and outputting an optimized target sensitivity score map; s6, inputting the optimized target sensitivity score chart into a condition image generator to generate a night vision image; and S7, discriminating the night vision image, optimizing generator parameters, and outputting an enhanced night vision image. According to the method, the night vision image is enhanced and generated by combining the multi-modal depth features and the improved badger algorithm.

The present invention relates to a split-type fusion sight, comprising a sight main body. An aiming assembly connecting base is arranged at the top of the main body; the aiming assembly connecting base comprises an engagement groove located on the front side, and an engagement base located on the rear side; an engagement block is arranged in the middle of the engagement groove, and a wire arranging base is arranged on the right side of the engagement base; the aiming assembly connecting base is further provided with connecting screw holes. The split-type fusion sight can fuse the low-light-level night vision or thermal imaging lens imaging with human eye observation of a target to assist in observing or determining the target, and then determines the aiming target by means of an aiming light point, thereby performing accurate shooting. In addition, the low-light-level night vision or thermal imaging lens imaging module is arranged above the sight main body, and is fixedly connected by means of the aiming assembly connecting base and connecting screws. It is convenient to replace the low-light-level night vision module or thermal imaging module, the sight main body does not need to be disassembled, and disassembly and replacement are more convenient.

In general, the disclosure describes techniques for joint spatiotemporal Artificial Intelligence (AI) models that can encompass multiple space and time resolutions through self-supervised learning. In an example, a method includes for each of a plurality of multimodal data, generating, by a computing system, using a first machine learning model, a respective modality feature vector representative of content of the multimodal data, wherein each of the generated modality feature vectors has a different modality; processing, by the computing system, each of generated modality feature vectors with a second machine learning model comprising an encoder model to generate event data comprising a plurality of events and / or activities of interest; and analyzing, by the computing system, the event data to generate anomaly data indicative of detected anomalies in the multimodal data.

The invention discloses a traffic safety facility night vision evaluation method and system, and relates to the technical field of image processing, and the method comprises the steps: obtaining a to-be-evaluated traffic safety facility image; if the to-be-evaluated traffic safety facility image is the to-be-evaluated traffic sign image, determining a retroreflection coefficient of each color area of a traffic sign in the to-be-evaluated traffic sign image; based on the retroreflection coefficient and the gray value uniformity of the specific distribution area of the traffic sign, performing night vision evaluation on the traffic sign; if the to-be-evaluated traffic safety facility image is a to-be-evaluated traffic marking image, determining a retroreflection brightness coefficient of a traffic marking in the to-be-evaluated traffic marking image and gray value uniformity of a specific image area where the traffic marking is located; and performing night vision evaluation on the traffic marking based on the retroreflection brightness coefficient and the gray value uniformity of the specific distribution area of the traffic marking. The traffic safety facility night vision detection method is high in detection precision and high in reliability.