157 results about "Ghosting" patented technology

The invention, which relates to the technical field of image processing, discloses a method for converting a 2D image into a 3D image, comprising the following steps: step 1, obtaining a 2D image; step 2, monocular depth estimation is carried out on the 2D image to obtain a relative depth map; 3, determining the longitudinal depth and the zero parallax surface of the scene according to the content of the 2D image; 4, carrying out value domain transformation on the depth map; 5, calculating the parallax of each pixel of the 2D image according to the transformed depth map, and then rendering an image of a virtual viewpoint according to the parallax; and step 6, repairing the cavity. According to the method for converting the 2D image into the 3D image, the watching experience is improved, the stereoscopic impression is enhanced, the ghosting phenomenon is reduced, and the proper proportion scale is kept; the conversion efficiency and the automation degree are improved, and manual intervention is reduced; meanwhile, the generalization ability is enhanced; in addition, the hole repairing effect is optimized, so that the converted 3D image is more natural and perfect.

The invention relates to a video snapshot compression imaging reconstruction method and system. The method comprises the following steps: inputting a video frame sequence and a time-varying mask set thereof into a measurement model to obtain initial estimation; constructing a reconstruction network which comprises a feature extraction module, a gating residual network module and a video reconstruction module; the feature extraction module comprises two three-dimensional convolution layers, each three-dimensional convolution layer is connected with an activation function, and the feature extraction module extracts initial features from the initial estimation; inputting the initial features into a gating residual network module, and outputting reconstruction information features; and the video reconstruction module fuses the reconstruction information features, and performs up-sampling and detail refining to reconstruct a video sequence. According to the method, on the premise that parameters and computing power are hardly increased, ghosting and flickering are effectively restrained, the stability of long-time reconstruction is improved, and an effective scheme is provided for SCI reconstruction with the high compression ratio, the super-definition resolution ratio and the long sequence.

The invention belongs to the technical field of vehicle-mounted HUD imaging quality. The invention provides an HUD ghosting simulation system and a use method thereof. According to the embodiment of the invention, the HUD optical module is used for generating the image source, and the image source is emitted to the windshield through the reflector assembly; performing ray tracing by using a data acquisition module to acquire a ray direction, a human eye position and a wedge-shaped angle of the wedge-shaped film; utilizing a data processing module to obtain a ghosting value according to the light direction, the human eye position and the wedge angle; sequentially changing the light-emitting point position, the human eye position and the wedge angle of the image source PGU, and repeatedly calculating ghosting values to obtain a plurality of groups of ghosting values; and analyzing the multiple groups of ghosting values to obtain the optimal wedge-shaped film. According to the method, the complex formula calculation process is avoided, and the problems that the ghosting calculation amount is increased and the calculation process is extremely complex in the face of large view field and multiple eye positions, so that complete analysis becomes very difficult are solved. The ghosting numerical values under various conditions can be rapidly analyzed, and the ghosting calculation accuracy, simplicity and speed are improved.

The invention discloses an image defect detection method and device and a computer readable storage medium, and the method comprises the steps: obtaining a to-be-detected image, the to-be-detected image comprises a plurality of modules, the modules comprise a first color module and a second color module, and the first color and the second color are two different colors; and detecting a module connection position between two adjacent modules with different colors by using a gradient integral projection method to obtain a defect detection result that whether the to-be-detected image has ghosting or not. In this way, efficient detection of ghosting can be achieved.

The invention discloses a dynamic scene-oriented multi-scale spatial-temporal feature fusion video super-resolution method, and belongs to the technical field of computer vision and image processing. The method comprises the following steps of: inputting an original video image into a trained video super-resolution network based on spatio-temporal feature fusion to obtain an optimized video image, and performing multi-scale extraction and fusion on video features by the video super-resolution network based on spatio-temporal feature fusion to obtain an optimized video image; according to the method, the problems of ghost shadow and optical flow caused by rapid change of an object are solved by utilizing a context residual learning network, and efficient feature extraction and fusion are realized by fully utilizing intra-frame space information and an inter-frame time relationship, so that the visual perception quality and the accuracy and robustness of super-resolution reconstruction are improved.

The application relates to a glass detection method based on deep learning and ghosting, and relates to the technical field of computer vision. The method comprises the following steps: performing glass detection based on a single original input image, the image being a single RGB image; extracting ghost features through a deep learning method of a backbone network based on the original input image to obtain a ghost area prediction map; connecting the ghost area prediction map with the original input image channel, extracting glass features based on the backbone network under the guidance of ghost clues, then performing glass feature decoding and glass area segmentation based on a convolutional neural network; and outputting a glass area prediction map. Compared with the prior art, the application performs glass detection based on a single image, and is more widely applicable. The backbone network can more accurately and efficiently extract ghost features and glass area features, and the ghosting phenomenon can be used to more accurately locate the glass area, obtain a high-quality glass area prediction map, and has good robustness.

The invention discloses a cross-domain HDR image dynamic ghosting removal method fusing statistical offset fuzzy membership, and the method comprises the steps: carrying out the ghosting removal of an LDR image sequence through employing a trained fuzzy statistical cross-domain ghosting removal model, and obtaining a ghosting-free HDR image; according to the model, after an input LDR sequence is subjected to preprocessing and feature extraction, a space context alignment module dynamically aligns non-reference frame and reference frame features through space-channel attention; meanwhile, the LDR image sequence is input into a statistical offset fuzzy membership module, and a membership graph is generated through sliding window statistical analysis and a fuzzy membership function; the aligned features are input into a multi-scale cross-domain cooperative processing module, multi-scale feature extraction and feature fusion are carried out, a frequency attention module is activated through membership graph gating, and global context modeling is introduced into a key region; and finally, outputting a high-quality ghosting-free HDR image. According to the method, fuzzy statistics and cross-domain processing are fused, and accurate ghosting removal and detail reservation in a dynamic scene are realized.

The invention relates to the technical field of video processing, in particular to a video fusion method and system based on a large model. The method comprises the following steps: acquiring a video stream for picture segmentation, identifying a moving target for each segmented picture, predicting a moving target track, matching a minimum pixel region, and determining a key frame; extracting features, and focusing an identification target in the key area; generating a static scene, aligning the recognized target and the scene, obtaining a dynamic shielding relationship, and outputting fused video data; the system comprises a dynamic picture division module, a multi-modal feature extraction module and a dynamic fusion reconstruction module. The method comprises the following steps: identifying a moving target for each segmented image, predicting a moving target track, matching a minimum pixel region, determining a key frame, focusing an identified target in the key region, aligning the identified target and a scene, obtaining a dynamic shielding relationship, and outputting fused video data; trajectory changes of the moving target are processed, and ghosting and dislocation of the fusion result are avoided.

The invention discloses a multi-lens acquisition video image processing method and system, and relates to the technical field of image processing, and the system comprises an image acquisition module, an image adjustment module, an audio acquisition module, an audio adjustment module, and a video detection module. According to the method and the system for processing the video images acquired by the multiple lenses, through an image acquisition module and an image adjustment module, when the video images acquired by the multiple lenses are identified, the range of the view field angle shot by the corresponding lens is identified, and the pictures acquired by the multiple lenses are sorted through the view field angle; the integrity of multiple pictures can be guaranteed, ghosting during synthesis of multiple images can be avoided through feature segmentation when the pictures are spliced, and sound effect positions of audios in the video pictures are adjusted by setting an audio acquisition module and an audio adjustment module and adjusting audio waveforms. And the audio sound effect position is matched with the video picture when the video is played.

The invention provides a palm center input method and device of intelligent wearable equipment, the intelligent wearable equipment and a computer readable storage medium. The palm center input method of the intelligent wearable device comprises the steps that a scene image is collected through an RGB camera of the intelligent wearable device for projection palm area recognition; after virtual input interface projection is carried out in the projection palm area, a first event image of a virtual input interface is acquired through an event camera of the intelligent wearable device; performing fingertip detection based on an event image set including the first event image through a trained fingertip detection model to obtain an operation fingertip position of the virtual input interface; and performing input processing based on the operation fingertip position and the virtual input interface. According to the method and the device, the problem of visual smear or ghosting caused by camera lag can be reduced, so that the operation fingertip position of a user in a high-dynamic scene can be accurately captured, and the interaction accuracy and fluency of the intelligent wearable equipment are improved.

The invention discloses a ground penetrating radar data fusion optimization method for tunnel detection. The method comprises the following steps: step 1, selecting an antenna frequency; step 2, cutting data; step 3, preprocessing the data; step 4, multi-frequency data space-time standardization; step 5, multi-frequency data fusion; step 6, Gaussian blur processing; and 7, image screening: selecting an optimized image with the best robustness. The method disclosed by the invention is specially used for tunnel detection radar data, interferences of metal davits, expansion joints and the like can be effectively removed, the fused multi-frequency data naturally transits near the boundary, the boundary and double images basically disappear, and the problems in practical application of tunnel engineering detection are effectively solved. According to the method, contradictory unification of large detection depth and high resolution is realized on the same image, targets such as steel bars and layers in the image are more easily and automatically identified by an artificial intelligence algorithm, and a technical foundation is laid for subsequent AI interpretation.

This information processing device comprises a motion compensation unit, an occlusion region detection unit, a ghost removal unit, and a DNN. The motion compensation unit performs motion compensation on a past frame inference result and generates a correction history. The occlusion region detection unit detects an occlusion region in the correction history in which a ghost may occur, on the basis of a motion vector indicating motion of a subject between frames. The ghost removal unit performs a ghost removal process with respect to the occlusion region. The DNN infers the current frame on the basis of a correction history in which the ghost removal process has been performed and a current, which is an image of the current frame subject to processing.

The invention discloses a multipath ghosting target elimination method for radar target imaging. The method comprises the following steps that S1, a radar emits electromagnetic waves and processes echoes to obtain output signals; s2, acquiring the total number of detected targets and distance information and Doppler information of each target; s3, drawing a distance Doppler image, and carrying out binarization to obtain a binarized image; s4, carrying out target collinear detection, and judging each detected collinear group; s5, sorting the multiple groups of collinear groups obtained in the step S4; s6, carrying out the judgment of a multipath ghosting target; and S7, eliminating the multipath ghosting target from the target set T. The invention also discloses a multipath ghosting target elimination device for radar target imaging. According to the method, the first-order ghosting and the second-order ghosting can be accurately searched and eliminated at the same time, the coping capacity of the radar for different-order multipath ghosting targets is enhanced, and the accuracy and the reliability of the radar for real target imaging are improved.

The invention discloses a binocular video stitching method based on suture line search, and the method comprises the following steps: S1, video collection and preprocessing: obtaining a video stream through employing a binocular camera, and carrying out the preprocessing of each frame of image; s2, a calibration stage: carrying out feature point extraction and grid construction on each video frame by adopting an improved grid optimization algorithm, and generating calibration data; s3, generating a lookup table: generating the lookup table according to the calibration data, and mapping each pixel to a new position; s4, suture line searching: performing suture line searching by using a suture line searching algorithm based on dynamic programming; s5, motion detection and suture line updating: calculating a gradient difference of a suture line area, judging whether a moving object passes through a seam or not, and if the moving object passes through the seam, updating the suture line; and S6, image fusion: carrying out average fusion on the seam region. According to the method, the improved grid optimization and dynamic programming algorithm is adopted, high-precision binocular video stitching is realized, and motion artifacts and ghosting phenomena are effectively eliminated.

The application provides an image registration data processing method and system, relates to the technical field of image registration, and obtains a plurality of structural feature images in a plurality of monochrome laser images; according to the plurality of structural feature images, a plurality of ghosting areas with excessive eye movement are obtained, each of the ghosting areas includes a corresponding ghosting floating image and a ghosting reference image; a feature point corresponding relationship is obtained; a plurality of feature point pairs with accuracy greater than a preset threshold are obtained, feature point matching processing is performed, and a processed ghosting floating image is obtained; pixel registration processing is performed, and a region registration image is obtained; a plurality of region registration images are aligned and fused, a reference image and a floating image are combined, and a registration image is obtained. The application solves the technical problems of the prior art, such as inconsistent image offset in the image acquisition process, low whole-image registration accuracy, and the like, and achieves the technical effects of correcting the partial image offset caused by patient eye movement and improving real-time registration accuracy.

The invention discloses an image processing method, an electronic device, a vehicle and a computer readable storage medium, and the method comprises the steps: obtaining vehicle-mounted images of at least two adjacent cameras of the vehicle, and projecting foreground region images of the at least two adjacent cameras to a first plane when detecting that a foreground object exists in the vehicle-mounted images, and splicing the foreground area images projected to the first plane to obtain a spliced foreground image. Therefore, the foreground image can be determined on the basis of the projection of the foreground area image on the first plane, so that the situation of defects such as ghosting or dislocation in the foreground image obtained by splicing can be avoided to a certain extent, and the quality of a panoramic image obtained by the foreground image can be guaranteed; and the user experience of the panoramic monitoring image system can be guaranteed.

The utility model provides an HDMI video multimode optical fiber SWDM transmitter, which relates to the technical field of transmission equipment, and comprises an optical fiber video extender, a transmitter, a receiver and an electric signal path, the transmitter is connected with an HDMI Source end, the receiver is connected with an HDMI Sink end, the transmitter and the receiver are connected through an optical fiber, and the problem that the HDMI high-definition line is only 15m in longest length and is not long enough is solved by adopting a mode of installing the optical fiber video extender. An HDMI signal is attenuated and the video quality is influenced when the HDMI signal exceeds 15 meters, but in daily work and life, a video is generally required to be transmitted to a place of dozens of meters and even hundreds of meters, so that the video signal is required to be prolonged and controlled, and when the existing HDMI extender is used for transmitting the video signal for a long distance, the image ghosting is easy to occur, and the video quality is influenced. And the definition and the fidelity of the video are difficult to guarantee, so that the user experience is reduced.

The invention discloses a through-the-wall radar ghosting identification and suppression method based on template matching, and the method comprises the steps: firstly, carrying out the matching of candidate targets at different positions of a radar image through the imaging templates of the targets at different positions, and identifying the ghosting and the targets according to the matching degree; furthermore, a ghosting mask is generated according to an identification result, so that the suppression of the ghosting is realized. The effectiveness of the algorithm is verified through simulation and actual measurement analysis. The method does not need any geometric prior information, and is a universal image domain ghosting identification and suppression method.

The invention discloses a video stitching method and device based on an embedded platform, and the method comprises the steps: collecting a video stream with an overlapping region through two cameras, carrying out the processing of the first frame data on the embedded platform, obtaining a homography matrix, and calculating the overlapping region; determining a suture line by using an optimal suture line algorithm, and performing color correction and fusion on the first frame by using an optimized histogram matching method and a fade-in and fade-out method; detecting a moving object by using a frame difference method, setting a current frame as an updated frame, an updated suture line and a color correction function when the moving object passes through the vicinity of the suture line, avoiding ghosting and blurring, and periodically updating a homography matrix in order to eliminate errors; and generating pixel mapping from the data of the first frame and the updated frame, storing a color correction function, directly performing coordinate mapping and color correction on other frames, accelerating a fusion process by using hardware, and finally displaying a spliced video on a display device in real time. The splicing quality is improved while the real-time performance is ensured, and the spliced image is quickly obtained and displayed on the display device in real time.

The invention relates to the technical field of mechanical conveying equipment, and discloses a machine vision-based electroplating defect real-time detection device, which comprises a conveyor belt, a following adjustment mechanism is arranged on one side of the conveyor belt, a protective shell is arranged on the outer side of the following adjustment mechanism, a camera device is arranged in the following adjustment mechanism, and the camera device is connected with the conveyor belt. A light supplementing device is further arranged in the following adjusting mechanism, an inductive probe is arranged on one side of the following adjusting mechanism, and a receiver is further arranged on one side of the following adjusting mechanism. According to the electroplating defect real-time detection device based on machine vision, through the arrangement of the following adjusting mechanism, in the movement process of the transmission belt, synchronous movement of an electroplated part and the camera device is achieved, the situation that the production rhythm is interrupted by the traditional process of stopping, detecting and re-conveying is avoided, the overall production efficiency is improved, and the production cost is reduced. Moreover, the problems of blurring and ghosting caused by relative movement are reduced, and the conditions of false detection and missing detection caused by poor image quality are reduced.

The invention discloses an electronic ink screen local refreshing method and system based on space-time prediction and waveform optimization, and relates to the technical field of electronic ink screen local refreshing, and the method comprises the steps: collecting user behavior characteristics and screen state data, inputting the data into a user behavior prediction module, and outputting a dirty region, a potential modification region and prediction confidence thereof; the pre-rendering candidate region is combined with the prediction confidence degree and then converted into a standardized data structure to be issued; the intelligent waveform optimization module outputs a target waveform parameter based on the extracted key features of the dirty region and the prediction confidence; the ghosting elimination module generates a reverse compensation waveform according to the target waveform parameter and the information of the dirty area, is used for eliminating ghosting, and finally indicates the display controller to refresh a screen and update display content; according to the refreshing method, the characteristics of no backlight and no stroboflash of the electronic ink screen are fully exerted, and a healthy programming learning environment is provided for young children; and asthenopia and visual impairment risks caused by long-time use are reduced.

Systems and methods for generating autocomplete text using a language model are disclosed. An image and text-prefix may be entered at an input field of a search application. The image is processed to generate an image description. The image description and the text-prefix signals may be used as input at a language model to generate an autocomplete text by the language model. A contextual history may also be included as input to the language model. The autocomplete text is an output by the language model based on the input at the language model. The auto-complete text may be a next-word ghosting.

The invention discloses a PS-OCT polarization artifact suppression method based on a cross coupling coefficient. Comprising two parts of pre-measurement based on matrix calculation and PS-OCT data processing based on a cross coupling coefficient, according to the pre-measurement, a dual-channel interference signal is obtained by scanning a wave plate through a PS-OCT system, and then a ghosting artifact displacement set and the cross coupling coefficient are obtained; in the data processing step, a PS-OCT data processing method based on a cross coupling coefficient is used for detecting a sample and processing a dual-channel interference signal, and finally a PS-OCT image without polarization artifacts is obtained. Through the cross coupling coefficient, the cross coupling effect generated by various polarization elements can be quantified, and accurate suppression of polarization artifacts is achieved; the cross coupling coefficient is obtained in advance through the detection wave plate, in actual imaging, the cross coupling coefficient does not need to be measured any more, and the speed of suppressing polarization artifacts is increased; on the premise that the original configuration of the system is not changed, the polarization artifacts are comprehensively suppressed.

The application discloses a panoramic depth high dynamic range imaging system and method based on compound eye structure, relates to the technical field of computational imaging and image processing, and synchronously collects and multi-scale motion estimation ensures the time sequence consistency between sub-images, effectively reduces the splicing dislocation and ghosting caused by the rapid movement or partial occlusion of an object, and improves the stability of a dynamic scene; an adaptive HDR fusion mechanism based on exposure difference and local features preferentially retains high-contrast unsaturated region details through intelligent weight distribution, overcomes the overexposure and underexposure problems under backlight or light mutation, and makes the output image naturally smooth in the bright-dark transition area; in addition, multi-scale depth synthesis and edge perception filtering work cooperatively, enhances the depth estimation accuracy of a low-texture area, avoids depth jumping and edge blurring, and guarantees the overall definition of the panoramic depth image; meanwhile, rolling shutter correction and space-time interpolation compensation further reduce dynamic ghosting and noise interference.

The invention relates to an image fusion method and device, computer equipment and a storage medium. The method comprises the following steps: by taking an original long frame as a reference frame, carrying out global alignment on an original short frame and the original long frame to obtain a global alignment short frame; a global ghosting map is generated based on the global alignment short frame and the original long frame, and a first motion area of the global alignment short frame relative to the original long frame is marked in the global ghosting map; and in the first motion area, based on a global ghosting map, fusing the global alignment short frame and the original long frame to obtain a first fusion frame. The image quality of the fused image can be improved by adopting the method.

The invention relates to optical artifact mitigation and content display enhancement. Various implementations disclosed herein include devices, systems, and methods for presenting content items (e.g., movies, television programs, homemade videos, etc.) on an electronic device, such as an HMD. Some implementations adjust content being displayed by an electronic device to mitigate optical module-based artifacts (e.g., ghosts). For example, in an HMD with a reflective refractive lens, the specular layer may leak some light, resulting in ghosting artifacts, which may be mitigated by adjusting brightness, dynamic range, contrast, light spillover, color, etc. Some implementations utilize content item perception-based adjustments (e.g., adjustments based on peak brightness of a scene in a movie being displayed within an augmented reality (XR) environment, etc.). Some implementations provide adjustments based on environmental perception (e.g., how dark ambient or transparent environment is) and / or optical module modeling. These adjustments may alter a particular content item and / or an environment in which the content item is presented.

Devices, methods, and non-transitory computer readable media are disclosed herein to repair or mitigate the appearance of unwanted reflection artifacts in captured video image streams. These unwanted reflection artifacts often present themselves as brightly-colored spots, circles, rings, or halos that reflect the shape of a bright light source in the captured image. These artifacts, also referred to herein as “ghosts” or “green ghosts” (due to often having a greenish tint), are typically located in regions of the captured images where there is not actually a bright light source located in the image. In fact, such unwanted reflection artifacts often present themselves on the image sensor across the principal point of the lens from where the actual bright light source in the captured image is located. Such devices, methods and computer readable media may be configured to detect, track, and repair such unwanted reflection artifacts in an intelligent and efficient fashion.

The present application discloses an image processing method, an image processing device, a terminal, and a non-volatile computer-readable storage medium. The image processing method includes: acquiring N frames of images, wherein N ≥ 2; determining a reference image in the N frames of images, and the remaining N-1 frames of images are images to be processed; generating N frames of de-ghosted images according to the reference image and the images to be processed; and fusing the N frames of the de-ghosted images to obtain a frame of fused image. In the image processing method, image processing device, terminal, and non-volatile computer-readable storage medium of the present application, since a selected reference image is used when generating a de-ghosted image, and the fusion process is performed on N frames of de-ghosted images, the role of the reference image is fully utilized, so that the ghost of the fused image is eliminated more thoroughly, thereby improving the clarity of the fused image.

A light detection and ranging (LIDAR) system transmits, towards a target, a set of chirp signals. The LIDAR system receives from the target, a set of adjusted chirp signals. The LIDAR system then determines, based on the set of adjusted chirp signals, a degree of ghosting mitigation to compensate for a ghost target appearing in a point cloud at a location where no real target exists.