252 results about "Multiple exposure" patented technology

The invention discloses a speed measurement method based on single-frame multiple exposure, and belongs to the field of hypersonic velocity field measurement. The implementation method comprises the following steps: recording equal time interval change of molecular marking in a flow field along with movement of the flow field through single-frame multi-time exposure imaging of an image enhancement camera, and realizing continuous and rapid acquisition of speed information within a short time after single-time marking. The morphological position after the time interval is determined according to the molecular marker, and the velocity field with spatial resolution in the flow field is extracted by mapping the marker before and after displacement, so that the velocity measurement precision is improved. Compared with other two-dimensional velocity field acquisition methods based on femtosecond laser molecular marker tracing velocity measurement, the method provided by the invention does not need a complex focusing lens combination, can obtain spatial positions of molecular markers at different moments only through isochronous continuous triggering exposure of a camera, thereby obtaining velocity flow field displacement information. And corresponding acceleration information can be further deduced according to the obtained velocity field. The method is especially suitable for hypersonic velocity field measurement.

The invention is applied to the technical field of low-light image enhancement, and particularly discloses a low-light image enhancement method based on multi-scale perception enhancement structure block decomposition, which comprises the following steps: firstly, carrying out SPD decomposition on a low-illumination image to obtain four components including perception gain, signal intensity, signal structure and average intensity; a perception gain component, a signal intensity component, a signal structure component and an average intensity component are respectively enhanced through an artificially set enhancement strategy, and the four enhanced components are fused into one image again through a multi-scale framework. According to the low-light image enhancement method based on multi-scale perception enhancement structure block decomposition, the image is subjected to adjustment enhancement after being decomposed so as to generate a result with rich information and vivid perception, a synthesized multi-exposure image is obtained by adopting simple logarithm stretching, the enhancement performance can be further improved, the enhanced image is more natural and real, and the image quality is improved. The method has advantages and effectiveness in the aspects of keeping detail information and keeping image consistency.

The invention relates to the technical field of wind power generation, in particular to a fan blade defect detection method and system based on a target detection model, and the method specifically comprises the steps: obtaining image data of a to-be-detected blade, and generating a fan blade defect image through employing an improved HP-VAE-GAN, so as to achieve the extension of a training set; in combination with a multi-exposure image fusion method based on a spatial frequency integration framework (MEF-SFI), the data quality is optimized; performing lightweight improvement on a YOLOV11 target detection model, and inputting the marked data set into the trained model to obtain a final fan blade state detection result; according to the method, the edge computing equipment is combined, the problems of large data acquisition amount, low transmission speed and the like are solved, and the accuracy, convenience and real-time performance of blade detection are improved on the whole.

The invention provides an image acquisition control method, device and equipment based on machine vision. The method comprises the following steps: selecting a high-frame-rate image sensor acquisition mode according to environment state parameters; adjusting exposure parameters of the high-frame-rate image sensor according to the selected acquisition mode; fusing the optical flow speed and the brightness of the image flow into a weighting factor according to the exposure parameters, and injecting the weighting factor into an image space to generate a scene partition mask; and the scene partition mask is aligned with the exposure images with different exposure parameters, and the exposure images are fused into a target acquisition image. Through the implementation of the scheme of the invention, the environment state parameters are generated in real time, the corresponding acquisition mode is selected, the exposure parameters are optimized, the optical flow and the brightness data are fused to generate the weighting factor, the scene partition mask is created, the multi-exposure image is aligned through the scene partition mask, the optimal exposure part of each area is accurately fused, and the high-quality target image is obtained. Therefore, the image acquisition efficiency is improved.

The invention provides a self-adaptive reverse multiple exposure phase fusion technology, and relates to the field of high-dynamic-range three-dimensional reconstruction. The method includes the following steps that firstly, a saturated pixel mask matrix is obtained by judging pixels of a high-reflection area, then uniform grey-scale maps are selected step by step through a gradient adjustment method to obtain the optimal local projection intensity, and local coding and decoding are conducted on the high-reflection area through the optimal projection intensity pattern. And replacing an invalid phase value in the high-SNR image with a local phase value under the optimal projection intensity through an edge matching and phase fusion technology, and obtaining high-quality complete three-dimensional imaging information through coordinate mapping after a complete phase diagram is obtained. According to the method, the optimal projection intensity is adaptively determined through a small number of patterns, meanwhile, the high SNR of imaging patterns is guaranteed, and high-precision complete three-dimensional imaging is carried out on an HDR object. Experimental results show that in a traditional method, a large number of point clouds are lost in a saturated pixel area, the imaging integrity and the measurement precision cannot achieve the normal imaging effect, and the algorithm of the invention shows high integrity and high point cloud density in a dark area and a high-reflection area.

The embodiment of the invention relates to a method, equipment and medium for photoetching simulation. The method proposed herein comprises: determining, from an initial optical signal, a plurality of optical signal components corresponding to a plurality of photolithography in a lithographic process; adjusting each optical signal component in the plurality of optical signal components based on the process parameters corresponding to the multiple exposures, so as to determine a target optical signal related to the photoetching process; and at least based on the target optical signal, determining the simulated morphology of the photoresist after the photoetching process.

The invention discloses a binocular multi-exposure steel rail visual perception method and device, and relates to the technical field of steel rail image processing, and the method comprises the steps: obtaining a low-exposure original image and a high-exposure original image of a steel rail shot by a binocular camera; dividing the low-exposure original image and the high-exposure original image into a plurality of blocks, and calculating block features of each block; the block features comprise local energy, local mass and spatial consistency; the local energy reflects an effective signal proportion related to laser stripes, the local quality reflects similarity among a plurality of sub-regions divided based on blocks, and the spatial consistency reflects a vertical distance between the blocks and a light band energy center; weighting and fusing the calculated block features to obtain a low-exposure initial weight map and a high-exposure initial weight map; and performing guided filtering weight correction on the low-exposure initial weight map and the high-exposure initial weight map, and performing weighted fusion pixel by pixel by using the corrected weight maps to obtain a fused image. The method can retain the significant features and spatial details in the image, and improves the fusion quality of the steel rail image.

The invention relates to a plate spring center point visual positioning method based on multi-model cooperation, and belongs to the technical field of plate spring center hole machining. Comprising the following steps: S01, acquiring a plurality of images under different exposure parameters, and fusing the multi-exposure images by using an IFCNN model to obtain an image with moderate exposure; s02, a YOLOV8 model is adopted to carry out target detection on the image, all the plate springs are accurately recognized, ROIs (Regions of Interest) of the plate springs are extracted, and each ROI only comprises a single plate spring; s03, performing fine segmentation by using U-Net, and extracting an accurate contour of a single plate spring; and S04, a binocular vision system is adopted, precise three-dimensional positioning of the center point of the plate spring is achieved through double-camera parallax calculation, and space coordinates (X, Y and Z) of the center point of the plate spring are obtained. According to the method, the space coordinates of the center point of the plate spring are accurately obtained in the plate spring punching process by combining the target detection and semantic segmentation methods, and automatic center punching of the plate spring plate is conveniently achieved.

The invention discloses a method and device for improving image quality and a storage medium. The method for improving the image quality comprises the steps of obtaining image data corresponding to each exposure mode in the same image collection scene based on at least two preset exposure modes; performing target detection processing on the image data corresponding to the at least one exposure mode to obtain object information of a target object in the image data; determining a target exposure mode from the exposure modes based on the object information and the exposure demand corresponding to the object information; and outputting the image data corresponding to the target exposure mode as target image data to obtain a high-quality image. According to the scheme, the high-quality image can be obtained from the image data of multiple exposure modes.

The invention discloses a method and device for quickly switching multiple working modes of a grating spectrometer, and the method comprises the steps: 1, laying a grating and a detector on a working turntable, and adjusting the grating and the detector to be concentric and coaxial; and step 2, rotating the working turntable and the grating respectively, adjusting different incident angles of the grating and adjusting the angle of the detector to match the working wave band. The grating, the camera system and the detector are mounted on the same rotary table, so that the consistency of an optical system in the mode switching process is ensured, and the grating, the camera system and the detector are ensured to be coaxial in the working mode switching process. The mode that the rotary table rotating motor drives the rotary table to rotate as a whole and the grating rotating motor drives the grating to rotate independently is combined, rapid switching of multiple working modes of the grating spectrometer is completed, and broadband wavelength coverage of the grating spectrometer with multiple exposure combined is achieved.

A method includes generating alignment maps for a first image frame having a first exposure level and a second image frame having a second exposure level different than the first exposure level. The method also includes generating, for the second image frame and a third image frame having a third exposure level different than the first and second exposure levels, shadow maps, saturation maps, and multi-exposure (ME) motion maps based on the alignment maps. The method further includes determining, based on the shadow maps, saturation maps, and ME motion maps, whether to perform machine learning-based denoising and, if so, on which image frame(s) to perform the machine learning-based denoising. In addition, the method includes updating at least one saturation map and at least one ME motion map for at least one of the second and third image frames depending on the image frame(s) on which the denoising is to be performed.

The invention relates to a metal workpiece surface image acquisition method and device based on multiple exposure. The acquisition method comprises the following steps: determining total exposure, and determining single exposure time and corresponding weight according to the total exposure; acquiring a surface image of the metal workpiece at each exposure time, and adjusting the surface image by using the corresponding weight; and combining a plurality of adjusted images to obtain a metal workpiece surface reflection-removed image. According to the method, a strategy of multiple times of irregular exposure is adopted, multiple times of short-time exposure is used for replacing one time of long-time exposure, a strong single light reflection area is avoided, light reflection is reduced, meanwhile, more image details are reserved, and the final image quality is improved.

The utility model discloses volume holographic optical waveguide exposure equipment, which can complete splicing exposure of a to-be-exposed area by switching a plurality of baffle plates to perform multiple exposure when the area of the to-be-exposed area is large, and can repeatedly utilize the baffle plates and mask plates for different types of optical waveguides or different shapes of to-be-exposed areas. The utilization rate of the baffle plate and the mask plate is increased to a certain extent, and the cost for manufacturing the baffle plate and the mask plate is reduced.

A system, method, and computer program product are provided for obtaining multiple exposures with zero interframe time. In use, an analog signal associated with an image associated with an image of an image sensor is received. Amplified analog signals associated with the image are generated by amplifying the analog signal utilizing gains. The amplified analog signals are transmitted to analog-to-digital converter circuits. The amplified analog signals are converted to digital signals utilizing the analog-to-digital converter circuits. The digital signals are combined to create a high dynamic range (HDR) image.

The embodiment of the invention provides a photo editing method and electronic equipment, and the method can carry out the multi-exposure special effect processing of a dynamic photo based on the main body detection information, motion detection and other metadata carried in the dynamic photo, and obtains a multi-exposure photo. Compared with a dynamic photo, a plurality of copies of the main body appear in the multi-exposure photo generated by the multi-exposure special effect processing, and the plurality of copies are fixed at different positions, so that a user can simultaneously see the plurality of copies moving to different positions at different moments in the multi-exposure photo, and the image originality is sufficient. Moreover, the user can obtain the photo with multiple exposure special effects through one-time editing operation, which is simple and efficient, and is beneficial to arousing the enthusiasm of the user to create by using the dynamic photo.

The invention discloses a bill identifier identification method, which comprises the following steps: continuously acquiring a plurality of exposure images of a target bill at different exposure times through acquisition equipment, and fusing the plurality of exposure images according to the pixel brightness of a plurality of image pixels in the exposure images to obtain a target exposure image corresponding to the target bill; performing image enhancement on the target exposure image to obtain a target enhanced image, determining target boundary information of the region of interest according to the target enhanced image and a boundary detection model, and determining a target mask region corresponding to the region of interest according to the target boundary information; the method comprises the steps of obtaining a gradient magnitude of each pixel in a target mask region, dividing the target mask region into a plurality of pixel regions, determining a dynamic threshold value of each pixel region according to the gradient magnitudes of the plurality of pixels in each pixel region, and generating a target image according to the plurality of dynamic threshold values, the bill identification of the target bill is determined based on the target image through the pre-trained image identification model, and the bill identification precision can be improved.

The invention relates to a multi-exposure deviation estimation lookup table construction method, correction method and system, and belongs to the technical field of display. Comprising the steps of designing a gray scale gradient graph; performing multi-exposure gradient image acquisition according to the gray scale gradient image to obtain an image data set; screening the image data set to obtain effective gray scale data; normalizing the effective gray-scale data according to respective exposure time, and synthesizing the effective gray-scale data into a complete gray-scale gradient image; performing section projection on the complete gray scale gradual change image to obtain a first Gamma table; normalizing the first Gamma table by using a standard Gamma table to obtain a second Gamma table; calculating the deviation between the standard Gamma table and the second Gamma table; and calculating a brightness correction value according to the respective exposure time and deviation of the effective gray scale data, and obtaining a lookup table. According to the invention, by collecting the accurate relative brightness, the accuracy of the compensation data is improved, so that the compensation effect is optimized.

The invention discloses a multi-exposure image fusion method and system for optimizing rendering quality and visual reality, and relates to the technical field of image processing. Comprising the following steps: splicing a multi-exposure image, and inputting the image into a convolutional neural network for parameter extraction to obtain a feature value; the feature values are put into a network model for end-to-end unsupervised learning, and a fusion image model is generated; the fusion image model is trained, in the training process, a loss function is used for continuously conducting back propagation iteration, learning content is updated, and the loss function is mean square error loss and structural similarity loss; and performing multi-exposure image fusion by using the trained fusion image model. According to the method, fusion operation can be carried out on an existing public multi-exposure image data set, texture details and brightness information of the multi-exposure image can be effectively extracted from a fused result, information loss and color distortion are effectively avoided after the texture details and the brightness information are combined, and a fused image better conforming to the visual effect of human eyes is formed.

The invention relates to the field of machine grid calibration, and discloses a machine horizontal grid calibration method and device, an overlay machine and a storage medium, the method is applied to the overlay machine, and the method comprises the following steps: obtaining an independent field pattern formed by exposure of a machine by using a horizontal grid calibration mask; the horizontal grid calibration mask comprises a plurality of overlay marks; obtaining a combined field pattern formed by multiple exposure of the machine table by using the horizontal grid calibration mask, wherein the combined field pattern comprises a plurality of overlay mark groups; according to an error value between an actual position of an overlay mark in the field pattern and a nominal position of a corresponding overlay mark on the horizontal grid calibration mask plate, determining a first grid error of the measuring end of the machine table; determining an overlay difference value between an inner overlay mark and an outer overlay mark in an overlay mark group in the combined field pattern to obtain a second grid error of the exposure end; and the first grid error and the second grid error are sent to the machine table, horizontal grid calibration is achieved, and the machine table and the machine hour are not occupied.

The invention discloses a fringe projection measurement method for a high dynamic range scene. The fringe projection measurement method can realize high-precision three-dimensional reconstruction of a complex reflection scene without human intervention. The method comprises the following steps: firstly, projecting pure gray-scale maps with different gray scales to calculate the maximum unsaturated exposure time of a camera for a scene, constructing a phase error model for a fringe pattern captured under exposure, and respectively calculating the optimal exposure time of each pixel point under phase error and light intensity constraint conditions; and then, obtaining required exposure times, masks and exposure time by using an iterative optimization algorithm of the masks. And finally, obtaining an optimal fringe pattern for three-dimensional reconstruction by automatically capturing and fusing fringe patterns at different exposure times. Compared with a traditional high-dynamic measurement method, the method has the advantages that high-quality multi-exposure fusion can be completed without human intervention, and high-precision and high-robustness three-dimensional measurement of a high-dynamic-range scene is realized.

A method includes flowing a first fluid through a first channel of a microfluidic apparatus and flowing a second fluid through a second channel of the microfluidic apparatus. The first fluid comprises biological material and a matrix material and is immiscible with the second fluid. The first and second fluids are combined at a junction to form droplets of the first fluid dispersed in the second fluid in a third channel. Multiple exposures of a droplet in the third channel are captured in a single image, comprising: illuminating a region of the third channel with multiple successive illumination pulses during a single frame of the imaging device; identifying the droplet and determining a velocity or a size of the droplet based on an analysis of the captured exposures; and controlling the flow of the first fluid or second fluid to obtain droplets of a target size or velocity.

The present application discloses an image registration processing method and device, belonging to the field of image processing technology. The method includes: extracting a feature sequence of a reference image and a feature sequence of a target image, wherein the target image is any image in a multiple exposure image sequence except the reference image; based on the feature sequence of the reference image and the feature sequence of the target image, calculating the global translation vector between the target image and the reference image; based on the global translation vector, updating the feature sequence of the target image to obtain a first image after registration processing; performing at least one registration processing based on the first image to obtain a registered image; wherein, in each registration processing of at least one registration processing, the image area of ​​the image to be registered is divided into multiple image sub-areas, and the feature sequence of the image to be registered is updated by the local translation vectors of the multiple image sub-areas, and the image to be registered is the image obtained after the last registration processing.

The application discloses a kind of based on multiple exposure generation fusion's low-light image enhancement system, belong to low-light image enhancement technical field.System includes: adaptive multiple exposure adjustment module (AMEA), joint prediction gamma coefficient, linear modulation factor and compensation parameter, to input low-light image carries out nonlinear and linear combination transformation, generates multiple luminance, contrast and different color response multiple exposure candidate image;Multiple exposure fusion module (MEF), original low-light image and candidate image channel splicing are carried out, and preliminary enhancement image is obtained by fine-grained weighting fusion of channel fusion coefficient and introduction of perception compensation parameter correction;Color refinement module (CRM), using encoder decoder structure and introducing fast fourier representation in bottleneck layer, realize spatial domain and frequency domain joint modeling, carry out global color calibration and local detail optimization to preliminary enhancement image.The overall network uses lightweight design such as depth separable convolution and dense connection, inference is simple, and can be run in real time in edge device.The application generates by adaptive multiple exposure, structure constraint fusion and frequency domain refinement, effectively restores dark texture, suppresses over-enhancement and color deviation, improves visual naturalness and robustness in complex low-light scene.

The invention discloses an accurate correction monitoring method based on a VR panoramic position and map coordinates, which belongs to the field of monitoring calibration methods, and comprises the following steps: constructing a high-precision three-dimensional geographic information model comprising a building contour, a ground marker and a high-altitude suspension through multi-modal data fusion of a laser radar three-dimensional point cloud and a VR panoramic image; meanwhile, a multi-exposure synthesis technology is adopted, dynamic object interference is effectively eliminated, image data quality is improved, multi-channel ResNet50 coding of visible light texture features and infrared heat source features is combined, and high-precision geometric feature matching is achieved through cosine similarity matching and Delaunay triangulation verification; a grading early warning mechanism is set to be a three-level early warning mechanism, differential safety strategies can be achieved, and the accuracy of early warning mechanism triggering conditions and the distinction of triggering execution mechanisms are improved.

The invention relates to an exposure sequence adaptive optimization method and device for multi-view automatic measurement, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring an original exposure time sequence of a plurality of viewpoints; the original exposure time sequence comprises a plurality of exposure segments, and each exposure segment corresponds to one viewpoint; calculating similarity data among the exposure segments, and grouping the exposure segments according to the similarity data to obtain a plurality of initial exposure groups; for each initial exposure group, re-grouping the exposure segments at the boundary position to obtain a plurality of boundary grouping results, and calculating grouping cost data for each boundary grouping result; and selecting a target grouping result from the boundary grouping results according to the grouping cost data, optimizing the target grouping result according to the grouping cost data to obtain a plurality of target exposure groups, and calculating the exposure time of each target exposure group. The method can shorten the measurement period.

The utility model discloses a laser lamp debugging and calibrating tool for a mobile CT, relates to the technical field of medical instruments, and can solve the problems that a laser of an existing mobile CT is very difficult to debug and calibrate, exposure needs to be conducted for multiple times in the debugging process, consumed time is long, and efficiency is low. The laser lamp debugging and calibrating tool of the mobile CT comprises a tool body, the tool body comprises an installation section used for being installed on an equipment rotating disc and a calibrating section used for debugging and calibrating the position of a laser lamp, and the installation section is fixedly connected with the calibrating section. Wherein the calibration section comprises a first calibration surface and a second calibration surface which are parallel to each other and are used for facing the two correlation laser lamp main bodies respectively; and the calibration structures are arranged on the first calibration surface and the second calibration surface in a mirror symmetry manner.

The invention relates to the technical field of image processing, in particular to a dynamic target pose measurement method based on a multiple exposure technology, which comprises the following steps: firstly, arranging a cooperative marker on a target object, and determining feature points on the target object; obtaining a feature point coordinate group of the target object at two continuous moments, and further calculating a feature point change speed; continuously acquiring a measurement image group of the target object at the next moment; by taking a first image in the measurement image group at the moment as a reference, compensating the coordinates of the feature points in the first image in combination with the change speed of the feature points so as to obtain a compensated feature point image coordinate set; and finally, combining the feature point image coordinate set to calculate the pose of the target object. According to the invention, target feature detection is carried out through the plurality of continuously acquired images, and the feature points are compensated, so that the pose calculation accuracy is improved, and the influence of feature misalignment among the plurality of images caused by target motion on the precision is reduced.

The application discloses an automatic high-reflective object three-dimensional measurement method based on reinforcement learning, constructs a multiple-exposure-time sequence prediction model based on reinforcement learning based on an irradiance map, realizes fast and automatic generation of the multiple-exposure-time sequence, and compared with a traditional method, comprehensively balances the relationship among exposure time, exposure frequency and image measurable area based on reinforcement learning, realizes stable and fast prediction of the multiple-exposure-time sequence, and achieves global optimization of the three, and the measurement effect of the high-reflective part is improved. Further, the irradiance is quickly and stably predicted based on a single image by constructing an irradiance prediction network, compared with the traditional method, the number of pictures required by the multiple-exposure-time sequence is reduced, and the measurement speed is improved.

A method includes obtaining, using at least one image sensor of an electronic device, a first image frame and multiple second image frames of a scene. Each of the second image frames has an exposure time different from an exposure time of the first image frame. The method also includes generating, using at least one processor, blur kernels indicating a motion direction of the first image frame using an optical flow network. The method further includes refining, using the at least one processor, the blur kernels using a convolutional neural network. In addition, the method includes generating, using the at least one processor, a target image frame of the scene using the refined blur kernels and occlusion masks for the second image frames.

The present invention provides a calibration method and system for a self-closed-loop pixelated headlamp detection device, which belongs to the field of vehicle light control technology. The method includes: setting the exposure mode of an imaging colorimeter to a multiple exposure mode to collect a brightness image of a self-closed-loop pixelated headlamp to be detected; completing the calibration of the headlamp installation position based on the coordinates of the feature points of a pattern with feature points projected by the self-closed-loop pixelated headlamp; performing pixel compensation on the pattern with feature points based on the center coordinate position of the feature points to complete the calibration of the light pattern area of ​​the self-closed-loop pixelated headlamp; using a polynomial fitting to measure the effect of junction temperature on illuminance to complete the calibration of the self-closed-loop pixelated headlamp illuminance. This method solves the problem that the traditional solution cannot accurately identify the light pattern contour due to virtual light and the problem of poor repeatability of illuminance testing.