746 results about "High definition" patented technology

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 present invention provides an automatic focusing method, an electronic device, and a readable storage medium. The automatic focusing method comprises: using a target detection model to detect a target object in an image frame acquired at an initial focal length by an optical imaging device to be focused, so as to acquire a target object detection result; on the basis of the target object detection result, determining whether a target object is present in the image frame; if yes, determining an actual object distance on the basis of the target object detection result and the initial focal length, and on the basis of the actual object distance and a mapping relationship between the object distance and an optimal imaging focal length, determining the optimal imaging focal length; and if not, using a preset search algorithm to search for a focal length until an image having the highest definition value is found, and using a focal length corresponding to the image having the highest definition value as the optimal imaging focal length. The present invention primarily employs a deep learning-based automatic focusing method, supplemented by an image definition evaluation method. Compared with traditional passive focusing methods, the present invention greatly improves the focusing efficiency. Compared with traditional active focusing methods, the present invention eliminates a need for adding an additional optical ranging component, ensuring that the imaging device has a simple structure and a low cost.

In various examples, training sensor data generated by one or more sensors of autonomous machines may be localized to high definition (HD) map data to augment and / or generate ground truth data—e.g., automatically, in embodiments. The ground truth data may be associated with the training sensor data for training one or more deep neural networks (DNNs) to compute outputs corresponding to autonomous machine operations—such as object or feature detection, road feature detection and classification, wait condition identification and classification, etc. As a result, the HD map data may be leveraged during training such that the DNNs—in deployment—may aid autonomous machines in navigating environments safely without relying on HD map data to do so.

The invention discloses a naked eye 3D transparent display imaging system, and relates to the technical field of 3D transparent imaging. The method comprises the steps that a multi-scale parallax layer construction module is used for decomposing a multi-scale parallax layer and dividing regional images; the dynamic viewpoint prediction module is used for generating two-eye three-dimensional space coordinates through human eye parameters; the parallax scheduling mapping module is used for performing space mapping according to the binocular three-dimensional space coordinates to generate a target visual angle image; the background compensation module is used for carrying out brightness correction on the target view angle image to obtain a compensated view angle image; the directional light field regulation and control module is used for processing the compensation view angle image and generating directional light field information; and the full-layer fusion module is used for processing directional light field information, eliminating interface artifacts between layers and generating a naked-eye 3D transparent display image. Through multi-scale parallax construction, dynamic viewpoint tracking and multi-layer light field fusion, the visual angle adaptability and image fusion quality of naked eye 3D display are improved, and a transparent three-dimensional imaging effect with high immersion, high consistency and high definition is realized.

The utility model provides a line repairing type high-definition laser plate roller engraving device which comprises a machine frame, a supporting frame is fixedly installed on the top of the machine frame, an X-axis driving mechanism is arranged on the supporting frame, a Y-axis driving mechanism is installed at the moving end of the X-axis driving mechanism, an installation base is installed at the moving end of the Y-axis driving mechanism, and a line repairing type high-definition laser plate roller engraving device is installed on the installation base. A laser engraving head is fixedly mounted on the mounting seat, a rotary clamping mechanism used for concentrically positioning and clamping a plate roller and driving the plate roller to rotate is mounted on the rack through a distance adjusting mechanism, and a lifting mechanism capable of lifting the plate roller is arranged on the rack. The distance adjusting mechanism is matched with the rotary clamping mechanism to clamp the printing rollers with different lengths, and during clamping, the axis line of the printing roller can be quickly positioned, so that the axis line of the printing roller and the axis line of the rotary shaft rod are positioned on the same straight line, and the engraving precision is further ensured.

The invention relates to the technical field of computers, in particular to a general traffic image generation method for solving unbalanced network traffic classification, which comprises the following steps of: arranging and combining original network traffic into a session stream according to a time sequence based on a session stream mode, and converting the session stream into an image by taking a data packet as a unit. Converting the effective load of each data packet into a grayscale image; the SCGAN is used for training; eliminating noise by adopting a convolution noise reduction auto-encoder, and performing high-definition reconstruction on the generated flow sample; and combining a minority of types of traffic image samples generated through high-definition reconstruction with the original real traffic samples. According to the method, when the data packets are converted into the traffic images, the time sequence dependency relationship of the network traffic is reserved, the structural features among the data packets in image representation are also reserved, a balanced new network traffic data set is constructed, the authenticity and diversity of the data set are kept, and the generalization ability and effect of the model are improved.

Methods and systems for generating a HD map and lane trajectory for an autonomous vehicle based on an SD map. Images from one or more image sensors mounted on a vehicle are received. Via a vehicle processor, perception data is generated based on the received images, wherein the perception data provides a representation of an environment proximate to the vehicle. A standard definition (SD) map corresponding with the environment proximate to the vehicle. The vehicle processor generates a high definition (HD) map corresponding with the environment proximate to the vehicle based on the SD map and the perception data. The vehicle processor also generates lane-level trajectory associated with a planned route for the vehicle utilizing the HD map.

Systems and methods for generating 3D scenes include a masked red, green, blue, depth (RGBD) input, which is separated into a masked RGB input and a masked depth input. The masked depth input is compressed. The masked RGB input is compressed. A high definition (HD) map control signal is generated for a depth stream, and an HD map control signal is generated for an RGB stream. A depth output is generated based on inputs from the depth stream, the HD map control signal for the depth stream, text encoder, and random sampled noise. An RGB output is generated based on inputs from the RGB stream, the HD map control signal for an RGB stream, text encoder, and random sampled noise to train a dual stream diffusion network.

A navigation method and apparatus, and an intelligent driving device are provided. The method includes: determining a lane-level topology of a road between a current location and a target location of an intelligent driving device based on a road-level topology and a lane quantity; determining a feasibility of each lane-level path of at least two lane-level paths from the current location to the target location based on the lane-level topology; and generating first navigation information based on a current lane in which the intelligent driving device is located and the feasibility of each lane-level path, where the first navigation information indicates a first lane-level path from the current location to the target location. The method may be applied to intelligent driving devices like new energy vehicles or electric vehicles, enabling lane-level navigation without a high definition map, improving navigation precision.

The invention relates to a broadband polarization multiplexing imaging metasurface which combines a newest machine learning algorithm and an advanced optical simulation technology and aims at achieving broadband high-definition and polarization multiplexing imaging effects. Meanwhile, the complete process of the metasurface from concept proposing to final design is elaborated, and by accurately developing machine learning model training and performing optical simulation verification, the polarization multiplexing far-field imaging metasurface in the same wavelength range is heart-shaped under x polarization and round under y polarization, and the metasurface is in the shape of the heart. It is ensured that the metasurface has excellent imaging performance in different polarization states. The innovative design not only improves the imaging quality, but also expands the application potential in various optical systems.

The invention discloses an ultrahigh-definition panoramic image adaptive HDR fusion method based on data driving, and relates to the technical field of digital image processing, and the method comprises the steps: carrying out the coarse alignment and high dynamic range fusion of a low-resolution line graph sequence, and generating a low-resolution HDR panoramic image; carrying out sharpening processing on the low-resolution HDR panoramic image to obtain a low-resolution sharpened HDR image, and meanwhile, obtaining a multi-scale residual spectrum generated by sharpening; performing up-sampling on the multi-scale residual spectrum, and performing small-sample element learning fine tuning on the weight prediction network in combination with the low-resolution sharpened HDR graph to obtain a fine-tuned weight prediction network; performing weight prediction and layer-by-layer fusion on the registered high-resolution tile sequence on a multi-scale pyramid based on a fine tuning weight prediction network model; according to the method, the sharpening processing is implemented on the low-resolution HDR panorama, and the multi-scale residual spectrum is extracted, so that the detail sensitivity and adaptability in a complex scene are improved.

The invention discloses a process pipeline micro-vibration motion amplification detection method based on automatic tracking and deconvolution, and the method comprises the steps: carrying out the automatic frame selection of a vibration abnormal region through an inter-frame difference method, tracking displacement through combining with an LK optical flow method, and analyzing a frequency spectrum, so as to adaptively determine an amplification frequency band; performing vibration signal enhancement by selecting an Euler or phase video motion amplification technology according to the environmental complexity; and further converting the RGB image into an HSV color space, inhibiting motion blur and artifacts by adopting confocal deconvolution, and finally synthesizing a high-definition amplified video. The method has the advantages that automatic recognition of the vibration area and the frequency band is achieved, and the detection efficiency is improved; the image quality is remarkably improved through deconvolution post-processing, and noise interference is avoided; complex industrial environments are compatible, reliable technical support is provided for non-contact pipeline health monitoring, leakage and explosion accidents are effectively prevented, and the service life of facilities is prolonged.

The invention relates to the technical field of image processing, in particular to a multispectral imaging recognition method and device for mountain tunnel lining corrosion defects. According to the method, an infrared spectrum image is taken as a reference image, image registration is carried out on an acquired visible spectrum image, and a visible spectrum image A and an infrared spectrum image B are decomposed through an NSST function to obtain a low-frequency sub-band and a high-frequency sub-band; the method comprises the following steps of: acquiring a low-frequency sub-band and a high-frequency sub-band, fusing the acquired low-frequency sub-band and high-frequency sub-band to acquire a high-frequency sub-band fused image and a low-frequency sub-band fused image, and reconstructing the low-frequency sub-band fused image and the high-frequency sub-band fused image through NSST inverse to acquire a fused image, so that the fused image has higher definition and contrast in various surface defects, and the image quality is improved. The detail texture information of the visible light image and the thermal radiation information of the infrared image are fully fused, the low-contrast defect features are better highlighted, and high-quality data support is provided for subsequent defect detection.

The invention discloses a high-definition real-time digital video monitoring system for realizing abnormal behavior recognition, relates to the technical field of communication, and solves the technical problem of improving the abnormal behavior recognition capability. The system comprises a video acquisition module, a preprocessing module, an analysis module, an abnormity determination module, an alarm module, a storage management module and a dynamic interaction module. According to the invention, the dynamic range of video acquisition is optimized through a quantum dot sensor array technology and an ambient light adaptive adjustment technology, multi-target detection tracking is realized through a YOLOv5 algorithm and a DeepSORT algorithm, and behavior characteristics are extracted in combination with a space-time diagram convolutional network. And through a rule and lightweight deep learning abnormity determination module, the identification accuracy is improved so as to ensure stable operation and real-time response capability in a complex scene. And the real-time identification capability of the digital video is greatly improved.

Systems and methods for generating 3D scenes include a masked red, green, blue, depth (RGBD) input, which is separated (1602) into a masked RGB input and a masked depth input. The masked depth input is compressed (1604). The masked RGB input is compressed (1606). A high definition (HD) map control signal is generated (1608) for a depth stream, and an HD map control signal is generated (1610) for an RGB stream. A depth output is generated (1616) based on inputs from the depth stream, the HD map control signal for the depth stream, text encoder, and random sampled noise. An RGB output is generated (1618) based on inputs from the RGB stream, the HD map control signal for an RGB stream, text encoder, and random sampled noise to train a dual stream diffusion network.

The present disclosure relates to the field of optical lens, and discloses a camera optical lens, including from an object side to an image side: a first lens having positive refractive power, a second lens having negative refractive power, a third lens having negative refractive power, a fourth lens having positive refractive power, a fifth lens having negative refractive power, a sixth lens having positive refractive power, and a seventh lens having negative refractive power; and the following relational expressions are satisfied: −0.300≤Sin(A1.0out14)*R14 / f7≤0.003; 1.05≤(f1+f2+f3+f4) / (f5+f6+f7)≤2.30; −1.40≤Sin(A0.8out8)*R8 / f4≤0.10. The camera optical lens according to the present disclosure has excellent optical characteristics of sufficient aberration correction, large aperture, wide-angle, ultra-thin, diversified structural design, and high sensor matching, and is particularly suitable for a mobile phone camera lens assembly and a WEB camera lens which are composed of camera elements such as CCD, CMOS with high definition and a vehicle-mounted lens.

The invention provides a scene multi-focal-length target video coding method. The method comprises the following steps: determining key targets which need to be subjected to key recognition; setting a zoom video recording system and a plurality of fixed-focus video recording systems; according to image data and position information, matching the same key targets in the zoom camera video frame and each fixed-focus camera video frame; and fusing the obtained image data with the highest definition of the key target to the position of the same key target in the zoom shooting video frame. The invention provides a scene multi-focal-length target video coding method, which is a method capable of enhancing the definition of a plurality of specific targets in a video recording system, and specifically, a zoom video recording system and a fixed-focus video recording system are used for cooperatively working, and specific targets in a fixed-focus system and a zoom system are intercepted; the target with the highest definition is calculated through an algorithm, and then the target data is fused into the frame of the zoom video stream, so that a plurality of targets of the zoom video stream can keep high definition.

A lighting device for a motor vehicle, in particular a high-definition headlamp, includes an imaging component that has an active surface on which light-emitting diodes or laser diodes are arranged in a matrix to generate pixels in a light distribution in a targeted manner, and a projection lens with which the light emitted from the active surface is projected outward from the motor vehicle when the lighting device is in operation. The lighting device is designed to switch the projection lens from a first setting to a second and from the second setting to the first. The projection lens has a first focal length in the first setting, and a second focal length in the second setting, which is greater than the first focal length.

The invention discloses an X-ray imaging system and a machine head thereof. The machine head comprises a bulb tube and a beam limiting device. The beam limiting device is provided with an X-ray limiting device, a reflecting part, an image projection device and an adjusting device, the image projection device can project imaging light, and the imaging light is reflected to the X-ray limiting channel by the reflecting part and penetrates out of the beam limiting device through the X-ray limiting channel to form an image. The image projection device replaces a traditional LED light source, and because the image projection device can form an image, the image formed by the image projection device can comprise a light field used for representing an irradiation area of X rays and light field additional information used for displaying medical auxiliary information in the light field. The light field is imaged by the image projection device and is higher in definition. The light field additional information is beneficial for doctors to know more information during medical operation. The adjusting device is used for adjusting the emitting direction of imaging light of the image projection device so that the light field projected by the image projection device can coincide with the irradiation area of the X-rays.

The invention discloses a high-performance anti-dazzle coating as well as a preparation method and application thereof. The core technology of the coating is to form a uniform film with a micro-nano composite structure on the surface of a base material through a self-assembly film forming process by utilizing nano quartz powder with specific particle size distribution. The coating has excellent optical performance, the light transmittance reaches up to 92% or above, and the haze is strictly controlled to be 5% or below. The unique microstructure can effectively scatter strong incident light (such as sunlight and vehicle lamps), significantly reduce dazzling glare, and maintain high definition of the base material and high reflective (or self-luminous) visibility of the identification itself, so that an observer can clearly and comfortably identify target information. The method is simple in process, controllable in cost, environment-friendly and particularly suitable for the fields of traffic safety, public facility identification, display screen protection and the like.

The invention discloses a large-target-surface high-resolution unmanned aerial vehicle lens and electronic equipment. The lens sequentially comprises a first lens, a second lens, a third lens, a fourth lens, a fifth lens, a sixth lens, a seventh lens, an eighth lens and a ninth lens from an object side to an image side. The first lens has negative diopter, the object side surface of the lens is a convex surface, and the image side surface of the lens is a concave surface; the second lens has negative diopter, the object side surface of the lens is a concave surface, and the image side surface of the lens is a concave surface. The invention provides an innovative optical design for solving the problem that an existing unmanned aerial vehicle lens cannot give consideration to light weight, high definition, large target surface, large aperture and large field angle. Through the glass-plastic mixed design, the use number of glass lenses is reduced, and meanwhile, the unmanned aerial vehicle lens with a large target surface, a small size and high resolution is realized by matching with a sensor with a 1 / 0.98 inch target surface. The lens can meet the high resolution requirement of more than five million pixels, and the imaging quality is remarkably improved.

The present application relates to the technical field of image processing, and provides an image processing method and apparatus, a cell defect detection method and apparatus, and a device. Nonlinear stretching processing is performed on a cell region image of a cell to obtain a stretched image, and such processing can improve the contrast between levels of a cathode and an anode of the cell in the cell region image, thereby improving the imaging effect; an exponential function is used by a nonlinear stretching formula, such that a grayscale interval in the cell region image can be expanded, detail features are highlighted, the stretching effect can be improved, and images having higher definition can be provided for subsequent cell defect detection, thereby improving the accuracy of the cell defect detection.

The invention discloses a ship detection data set construction method based on unity, and the method is specifically implemented according to the following steps: step 1, creating a unity High Definition 3D project, and generating a unity WaterSurface water system in the project; 2, a ship model obtained through autonomous modeling or obtained from a network is imported into the unity WaterSurface water system in the step 1, and the ship model is adjusted to be located at a reasonable position; and step 3, a ship video picture is obtained in a screen recording or screenshot mode, a ship data set is enriched in a mode of adjusting ocean colors and illumination conditions and replacing a ship model, and a plurality of labels are adopted to meet detection requirements of special ships. The problems that in the prior art, a traditional real data set in a ship data set is difficult to collect, angles are incomplete, scene coverage is insufficient, and marking is difficult are solved.

The invention relates to the technical field of coal mining, in particular to a coal-rock interface detection device based on image recognition. According to the technical scheme, the coal rock interface detection device based on image recognition comprises a detection device body, an image recognition probe, a signal receiving module, an image analysis module, a positioning module and a mounting mechanism, the image recognition probe is arranged at one end of the detection device body, and the signal receiving module is arranged on the top face of the image recognition probe; according to the invention, the multi-modal image acquisition module, the integrated adaptive light source control unit, the multi-spectral imaging unit and the mechanical anti-shake unit are designed, and the adaptive light source can dynamically adjust the brightness according to the ambient light, so that the imaging stability is ensured; according to multispectral imaging, visible light and infrared data are synchronously collected, wave bands are switched in combination with an optical filter wheel disc, the coal rock interface spectral feature recognition capacity is remarkably enhanced, the device can still obtain high-definition and multi-dimensional images in the complex underground environment, and a reliable data basis is provided for subsequent analysis.

The invention discloses an image super-resolution reconstruction method based on multi-scale exposure normalization and double-branch feature aggregation, and relates to the technical field of image reconstruction, and the method comprises the steps: obtaining a to-be-processed image; constructing a super-resolution network model based on a Swin Transform architecture, performing feature reconstruction on the to-be-processed image through the super-resolution network model, and outputting a super-resolution image; wherein the super-resolution network model extracts shallow feature information of the to-be-processed image, exposure normalization processing is performed on the to-be-processed image based on the shallow feature information, and after color correction and feature enhancement are performed on exposure normalization features, the super-resolution image is mapped and reconstructed. According to the method, the problems of important detail missing, color distortion, structure distortion and the like in the image exposure correction process in an overexposure scene are solved, so that high-definition and high-resolution image reconstruction is realized.

Provided are methods for high definition map fusions for 3D object detection. Some methods described also include obtaining, with at least one processor, raster maps, vector maps, and point cloud data and extracting, with the at least one processor, features from the raster maps, vector maps, and point cloud data to generate respective bird's eye view (BEV) representations. The methods also include fusing, with the at least one processor, the BEV representation of the raster map features, the BEV representation of the vector map features, and the BEV representation of the point cloud features into a fused BEV image. Additionally, the methods include detecting, with the at least one processor, objects in the fused BEV image. Systems and computer program products are also provided.

The invention discloses a grayscale image translation motion blur recovery method and system based on optical flow guidance, and belongs to the technical field of image processing. A target area is determined based on a video stream H; calculating a translational motion vector field matrix between every two adjacent frames in the video stream H by adopting an optical flow method, obtaining a translational motion vector located in a target area, further constructing a track representation matrix for reflecting a motion track of a motion target generating translational motion, normalizing the track representation matrix to serve as a blurring kernel, and obtaining a motion vector field matrix; and translational motion blur of the target area is removed in a targeted manner. According to the method, the high-density time sampling information provided by the video stream H with the high frame rate and the low signal-to-noise ratio is utilized, and the complex translational motion track of the blurred image B with the low frame rate and the high signal-to-noise ratio in the exposure period can be accurately captured. The fuzzy kernel synthesized based on the accurate translational motion trails can highly approach a real physical fuzzy process, and an image with a high signal-to-noise ratio and high definition can be reconstructed.

The present application relates to a kind of road crack detection method, device and medium based on cross-modal feature fusion, method includes the following steps: obtaining the color feature and depth feature of road crack data, color depth feature is obtained by fusing color feature and depth feature, color feature, depth feature and color depth feature are input into the detection network based on cross-modal three-flow feature fusion network for detection;Wherein, cross-modal three-flow feature fusion network includes cross-modal interactive fusion module and global interactive module, color feature extraction module and depth feature extraction module extract the color feature and depth feature of road crack data respectively, color feature, depth feature and color depth feature are fused by improved cross-modal interactive fusion module, form comprehensive feature, again by global interactive module for splicing, obtain splicing result, and detection network obtains detection result based on splicing result.Compared with prior art, the present application has the advantages of high precision, high definition and the like.

A high-definition lamp unit contains a plurality of individually controllable pixels, and emits lamp beam having light distribution corresponding to states of the pixels. A first sensor is provided to enable detection of a dynamic component of a pitch angle of a traveling vehicle body. A controller shifts the level of a cut-off line CL of the light distribution up and down, corresponding to the dynamic component of the pitch angle of the vehicle body, with reference to a predetermined level defined as a base.

The invention provides an endoscopic image enhancement method and system, and relates to the technical field of medical image processing. The method comprises the steps that an endoscope image enhancement model composed of a local sensing network, a global color mapping network and a fusion network is constructed, details of a low-quality image are extracted through the local sensing network, colors of a high-quality image are learned through the global color mapping network, two-way features are integrated through the fusion network, and an endoscope enhancement image is output; and generating total loss through the total loss function to optimize the endoscope image enhancement model so as to output an endoscope image with high definition and real color. An end-to-end lightweight network is adopted, unified enhancement of extreme illumination coexistence scenes is completed at a time, and the visual consistency and diagnosis reliability of gastrointestinal endoscopic images are remarkably improved.