43 results about "Dynamic contrast" patented technology

The invention belongs to the technical field of image processing, and particularly relates to an MBR flat membrane surface physical damage visual identification method and system, and the method comprises the steps: carrying out the low-pass filtering of a microscopic gray image, so as to melt a micropore background; calculating a texture variation index based on the outlier degree of the gray values of the neighborhood pixel points and the neighborhood gray dynamic contrast gain; determining a damage aggregation weight by using a space attenuation accumulation value, and eliminating isolated noise points; the texture variation index and the damage aggregation weight are fused through a self-adaptive gating function, and damage confidence is generated; and finally marking a connected damage region based on statistical threshold binarization and morphological processing. According to the method, dense micropore interference can be effectively inhibited, and the physical damage identification precision is improved.

The invention discloses a multi-modal sentiment analysis model based on hierarchical adaptive cross-modal fusion, belongs to the field of natural language processing, and is used for solving the problems that in the prior art, multi-granularity sentiment feature extraction is insufficient, a cross-modal fusion mechanism is rigid, and the distribution difference between different-source modals is large. The method comprises the following steps: firstly, extracting features of texts, audios and visual modalities from original video data, and coding the features into advanced semantic features; secondly, multi-granularity information is fused through a hierarchical feature extractor to generate enhanced single-mode features; then, a self-adaptive cross-modal fusion network with a text as a core is adopted to realize bidirectional interaction and dynamic weighted fusion between modals; further, a dynamic contrast learning mechanism is introduced to align modal distribution in a unified potential space; and finally, inputting the optimized multi-modal features into a classifier and outputting an emotion analysis result. According to the model, through collaborative optimization of multi-granularity feature extraction, adaptive fusion and comparative learning, the accuracy of sentiment analysis and the robustness of the model are remarkably improved.

The invention provides a scoliosis X-ray image enhancement processing method, relates to the field of image enhancement, and introduces a bone shadow edge intensity modulation factor, constructs gray scale bone shadow dynamic contrast mapping, and realizes preliminary enhancement of a scoliosis X-ray image; extracting a centrum center point sequence on the centerline of the spine, introducing a parameter curvature, and constructing an abnormal gravity kernel function to enhance significant focusing of a high-curvature region and smooth suppression of a low-curvature region in the scoliosis X-ray image; according to the method, centrum distribution density mapping is established, a multi-scale attention response map is constructed, a multi-scale fusion weight is introduced, the multi-scale attention response map and a curvature guide saliency map are fused, and an enhanced scoliosis X-ray image is obtained, so that centrum edges, abnormal bending and density mutation regions are clearer, and clinical readability and diagnosis precision are improved.

The invention relates to the technical field of liquid crystal display screens, in particular to a liquid crystal display screen dynamic contrast optimization method and system. The method comprises the following steps: dividing a backlight module of a liquid crystal display screen into a plurality of backlight partitions arranged in a matrix, dividing a current frame display image into corresponding image sub-blocks according to the coverage area of the backlight partitions, and extracting the brightness statistical characteristics of each image sub-block to obtain an original brightness distribution matrix; driving the backlight module to perform primary display according to the original brightness distribution matrix, and generating a voltage correction value covering the full quantization bit width of the source driver; and performing cooperative adjustment of reducing the PWM duty ratio and improving the liquid crystal light transmittance on the next frame of to-be-displayed image based on the voltage correction value so as to complete dynamic contrast optimization of the display screen. According to the invention, accurate contrast optimization of the liquid crystal display screen under a dynamic working condition is realized through a cooperative adjustment mechanism of backlight and liquid crystal light transmittance, so that an optimized display picture subjected to double dynamic compensation is output.

The application discloses a double memory dynamic contrast learning clothes-changing pedestrian re-identification method. First, the pedestrian video sequence with an identity label is acquired, and a three-dimensional space-time feature map is extracted through a backbone network; then, spatial aggregation features and time sequence difference features are extracted from the feature map; then, the two types of features are projected to identity and time sequence subspaces respectively, and attention weighted aggregation is performed through double memory banks to generate identity enhanced features and time sequence enhanced features; a similarity priority and diversity completion strategy is used to construct a positive and negative sample set, and a weighted contrast loss is calculated to jointly optimize the double memory banks; a sliding average strategy with diversity regularization is used to update the memory prototype; finally, the double path enhanced features are adaptively fused to generate discriminative feature representation, and a pedestrian matching list is returned through similarity sorting. The application focuses on stable identity features independent of clothes through the design of double memory banks and the use of multiple memory prototypes combined dynamically to represent pedestrians.

The invention relates to the technical field of medical image processing, in particular to a fundus angiography image processing system. The system comprises a static atlas initialization unit, a dynamic state evolution unit, a kinetic parameter fitting unit and a fundus dynamics report generation unit. The system constructs an initial static anatomical atlas by acquiring a baseline frame and extracting a static anatomical structure; the core of the method is to analyze a dynamic contrast sequence frame by frame based on the atlas to obtain a time sequence evolution state atlas; under physiological prior constraints, the optimal physiological dynamic parameters are fitted by comparing model prediction with a time sequence evolution graph; and finally generating a fundus dynamics report containing the functional quantitative index and the focus activity heat map. The system can also take the kinetic parameters as historical priori and call the kinetic parameters in a future fitting task so as to dynamically adjust a constraint range and realize individualized closed-loop self-optimization; according to the method, the limitation of traditional static snapshot analysis is overcome, and accurate modeling can be carried out on complex physiological dynamic processes such as perfusion and permeation.

This invention relates to an MRI-based method for classifying benign and malignant intraductal lesions (IDLs) of the breast, comprising the following steps: Step 1) Extracting a set of clinical features from MRI images: age, ADC value, BI-RADS category, lesion shape, margin clarity, and TIC curve type; Step 2) Extracting radiomics features from the 3D lesion segments of the T1 DCE-MRI sequence; Step 3) Reducing the dimensionality of the radiomics features using the Lasso algorithm; Step 4) Fusing the dimensionality-reduced radiomics features with the clinical features into an input vector; Step 5) Outputting benign / malignant probability values ​​through a logistic regression model; Step 6) Applying stratification rules to BI-RADS 4A lesions: older patients or those with low ADC values ​​are marked as high-risk and biopsy is recommended; younger patients with high ADC values ​​are marked as low-risk and follow-up is recommended. This method solves the problem of current dynamic contrast-enhanced MRI's difficulty in accurately identifying BI-RADS categories, especially the BI-RADS 4A high-risk subgroup, thereby reducing missed diagnoses and over-biopsy. It is of urgent significance for overcoming the bottleneck of preoperative risk stratification in IPLs and guiding individualized clinical decision-making.

The application relates to the technical field of biosciences, and is a circRNA-disease correlation prediction model construction method and correlation prediction method based on dynamic contrast sampling linear and nonlinear feature resonance and related devices, which comprises the following steps: obtaining a training set and a test set; training a multi-view contrast learning DCFR-CDA model by using the training set; introducing a loss function during the training; ending the training when the value of the loss function is stable; obtaining a circRNA-disease correlation prediction model; testing the circRNA-disease correlation prediction model by using the test set; optimizing model parameters; and outputting a circRNA-disease correlation prediction model meeting test evaluation requirements. The application jointly applies a linear decomposition method and nonlinear decomposition methods of multi-layer perception decomposition and one-dimensional convolution decomposition to generate multi-view embedding compatible with global and local modes, thereby effectively improving the prediction accuracy of the model.

The present application relates to the technical field of display dynamic contrast optimization, and particularly relates to a display dynamic contrast optimization system and method. The method comprises the following steps: obtaining the luminance distribution state of a to-be-displayed picture in a current display period of a display screen, collecting the outputtable backlight luminance range of the display screen, and determining the luminance distribution reference of the to-be-displayed picture on the display screen; based on the luminance distribution reference, dividing the display picture into multiple display partitions, and combining the luminance change requirements of each partition to calculate the partition luminance change load degree; and according to the partition luminance change load degree, adjusting the contrast and luminance; the present application realizes the balance between picture level enhancement and display stability in the display dynamic contrast adjustment process by performing partition analysis on the display picture based on the luminance distribution reference.

This invention belongs to the field of image processing technology, specifically relating to a method and system for visual recognition of physical damage on the surface of an MBR flat sheet membrane. The method includes: low-pass filtering a microscopic grayscale image to melt the micropore background; calculating a texture variation index based on the outlier degree of grayscale values ​​of neighboring pixels and the dynamic contrast gain of the neighboring grayscale; determining damage clustering weights using spatial attenuation accumulation values ​​to remove isolated noise points; fusing the texture variation index and damage clustering weights through an adaptive gating function to generate a damage confidence score; and finally, marking connected damage regions based on statistical threshold binarization and morphological processing. This invention effectively suppresses interference from dense micropores and improves the accuracy of physical damage recognition.

The invention provides a boiler heating surface early warning method and system based on multi-dimensional dynamic comparison. The method comprises the following steps: constructing a multi-dimensional ledger database of a boiler heating surface; based on the multi-dimensional ledger database, utilizing a pre-trained ledger comparison model to carry out multi-dimensional dynamic comparative analysis to obtain a comparative analysis result; and generating corresponding risk early warning information according to the comparative analysis result, and visually displaying the risk early warning information. According to the boiler heating surface standing book comparison method, through real-time / historical data dynamic comparison, hidden defects such as heating surface pipe wall thickness reduction, over-temperature operation and creep over-limit are found in advance, and missing detection of manual troubleshooting is avoided. Meanwhile, the performance difference and the aging degree of the heating surfaces in different areas are quantified, empirical judgment is replaced, and effective data support is provided for maintenance strategies (such as pipe replacement / soot blowing adjustment).

The application discloses a method, system and computer readable storage medium for improving dynamic contrast. The application periodically acquires a picture displayed by a display, then acquires a brightness value of a pixel of the current display picture, calculates a brightness percentage of the current display picture, and adjusts the brightness value of the display according to the brightness percentage of the current display picture. Specifically, when the brightness percentage is 0%, the target brightness of the display is 0%; when the brightness percentage is less than N%, the target brightness of the display is N%, wherein N is an integer closest to the value of the brightness percentage, and the range of N is 1-100; and when the brightness percentage is 100%, the target brightness of the display is 100%.

Embodiments of the present application relate to display technology, and provide a projection display device and method. The projection display device comprises: an image processing unit, configured to determine the current scenario, and if the current scenario is a first scenario, generate, by means of a phase modulation channel in the image processing unit on the basis of an image signal, a first signal and a second signal that are synchronized with each other, wherein the first signal is used for representing the image content of an image frame of the image signal, and the second signal is used for representing the brightness of at least one partition in the image frame of the image signal; a display driving control unit, configured to process the first signal to obtain a first amplitude modulation driving signal; a display image phase execution unit, configured to process the second signal to obtain a phase modulation driving signal; and an imaging display unit, configured to perform imaging display on the basis of the first amplitude modulation driving signal and the phase modulation driving signal. The device provided by the present application improves the dynamic contrast of the projection display device.

The invention discloses a Mini-LED backlight display halo perception boundary determination method and system, and aims to solve the problem that a halo boundary in a high dynamic contrast display scene is difficult to objectively define. The method comprises the following steps: acquiring brightness distribution of a display area and a surrounding dark area in a dark environment; guiding an observer to determine a subjective halo boundary position under a standard observation condition; mapping the position to objective brightness data to extract a boundary brightness threshold value; and establishing a sensing boundary model based on multiple groups of peak brightness and boundary thresholds, wherein the sensing boundary model is used for stably determining a halation region which can be sensed by human eyes under different brightness, partition and dimming strategies. According to the method, the perception boundary is used for replacing a fixed absolute threshold value, evaluation consistency is remarkably improved, closed-loop association of subjective perception and objective data is achieved, and reproducible and computable standardized criteria are provided for halo evaluation, algorithm optimization and production line quality control.

This invention discloses a laser projection display method and system. The method involves configuring the micromirrors of a phase-modulated light device into a high-low periodic structure. Then, based on optical diffraction characteristics, the actual height of the phase-modulated light device under each stage of driving signals is measured. Next, an ideal height set for the micromirrors is defined, which changes linearly with the progressively increasing driving signals. The actual heights that are within a defined error range from the actual heights are identified. These actual heights are matched with the phase level to establish an approximately linear relationship between the driving signal and the changeable phase level. This allows the driving signal to be sent according to the desired linearized height distribution in subsequent designs, achieving an approximately linear adjustment relationship between the change in the actual micromirror position and the change in the ideal micromirror position, thereby improving the dynamic contrast adjustment effect.

The invention provides a cross-platform compatibility test method and device, equipment, a medium and a program product. The method comprises the steps of obtaining multi-modal operation data of a to-be-tested application in multiple test platform equipment; obtaining a first weight coefficient of the to-be-tested application, and obtaining a comprehensive multi-modal operation value according to the first weight coefficient and the multi-modal operation data; constructing a multi-modal comparison sample group based on comparison learning, calculating a dynamic comparison coefficient according to the multi-modal comparison sample group, and obtaining a test abnormal value according to the dynamic comparison coefficient and the comprehensive multi-modal operation value; obtaining a multi-modal feature generated when the to-be-detected application runs on the target equipment, obtaining a target running value according to the multi-modal feature, and determining a feature difference value according to the target running value and the comprehensive multi-modal running value; obtaining a standard difference threshold value and a standard abnormal value, and generating a dynamic difference threshold value according to the standard difference threshold value and the standard abnormal value; and whether the characteristic difference value exceeds the threshold value is judged, so that the cross-platform compatibility information of the to-be-tested application is obtained according to the judgment result, and the test report is generated, and therefore, the test efficiency and accuracy are improved.

A dynamic contrast-enhanced MRI reconstruction method may include: when preparing to inject a contrast agent and during injection thereof, using a DCE-MRI sequence to scan an imaging target, and using a high temporal resolution scanning parameter value pre-inputted by a user to acquire K-space data of each phase with high temporal resolution; based on the acquired K-space data of each phase with high temporal resolution, reconstructing an image of each phase with high temporal resolution; based on a low temporal resolution reconstruction parameter value pre-inputted by the user, subjecting adjacent K-space data of multiple phases with high temporal resolution to summing and averaging in a complex field, and subjecting K-space data obtained after averaging to image reconstruction, to obtain an image of each phase with low temporal resolution. Advantageously, images with high and low temporal resolution can be obtained simultaneously with just a single DCE-MRI scan.

The invention discloses a lightning arrester instrument data image recognition method, system and device and a medium, and the method comprises the steps: obtaining an original image of a lightning arrester instrument, adaptively adjusting collection parameters according to environment illumination, carrying out the geometric correction and quality evaluation, carrying out the dynamic contrast enhancement and multi-scale noise suppression through an illumination decoupling model, and generating a standardized image; inputting a lightweight mobile terminal target detection model, and positioning and cutting an instrument display area; enhancing the sub-images, extracting edge features, and judging the type of the instrument: if the sub-images are digital, segmenting character areas and identifying the character areas by using a private network to obtain initial readings; verifying validity in combination with a preset physical quantity reasonable range, and generating a final reading; and automatically associating a current inspection task, adding time, a position and an image index, storing into a local database through transaction operation, and supporting generation of a structured inspection report. According to the invention, the accuracy and efficiency of inspection work are improved, and the reliability and traceability of data are ensured.

The invention provides an SSVEP method based on a micro LED, and the method comprises the steps: obtaining a video signal, carrying out the preprocessing of the video signal, and storing the preprocessed video data; presetting a plurality of display areas, wherein the display areas display the video data according to a preset time interval; the time history is composed of a plurality of continuous display periods, and each display period is composed of a prompt period, a presentation period and an interval period; the display area has a plurality of shape and color combination modes. By designing an innovative stimulation presentation method, the dynamic contrast of visual stimulation is optimized, the recognition precision of a brain-computer interface system is further improved, an accurate time-history structure and frequency setting are adopted, it is ensured that presentation of each stimulation combination can excite brain response to the maximum extent, and the stability and accuracy of signals are improved.

The embodiment of the invention belongs to the display technology, and provides a projection display device and method.The projection display device comprises an image processing unit used for determining a current scene, and if the current scene is a high-contrast scene, a phase modulation channel in the image processing unit is used for performing phase modulation on the high-contrast scene; generating a first signal and a second signal which are synchronous with each other according to the image signal; the first signal is used for representing the image content of an image frame of the image signal, and the second signal is used for representing the brightness of at least one partition in the image frame of the image signal; the display driving control unit is used for processing the first signal to obtain a first amplitude modulation driving signal; the display image phase execution unit is used for processing the second signal to obtain a phase modulation driving signal; and the imaging display unit is used for performing imaging display according to the first amplitude modulation driving signal and the phase modulation driving signal. According to the equipment provided by the invention, the dynamic contrast of the projection display equipment is improved.

A method includes acquiring a series of images over time from a liver of a subject injected with a contrast bolus, wherein the series of images span multiple phases of the contrast-enhanced scan. The method includes inputting the series of images into a trained neural network framework and utilizing the trained neural network framework to separately segment an aorta and a portal vein from each image of the series of images. The method includes utilizing the trained neural network framework to select exact respective time points for at least an aortic phase and a portal-venous phase based on the aorta and the portal vein segmented in each image. The method includes outputting a first set of images associated with the aortic phase and a second set of images associated with the portal-venous phase based on the exact respective time points selected for the aortic phase and the portal-venous phase.

The application relates to an image processing method, a projection device and a storage medium, which comprises the following steps: acquiring a source image, determining a brightness parameter of the source image according to pixel information of the source image; determining a target light source brightness required for displaying the source image based on the brightness parameter of the source image; and making a light source module emit light with the target light source brightness; updating the brightness value of each pixel point in the source image based on the brightness parameter to obtain a target brightness matrix; modulating the source image based on the target light source brightness and the target brightness matrix to obtain a modulated source image, and making the projection device project and display the modulated source image. According to the application, the dynamic contrast of the image can be ensured while effectively reducing power consumption, and the overall viewing effect of the projection can be improved.

The invention discloses a clothes changing pedestrian re-identification method based on double-memory dynamic contrast learning. The method comprises the following steps: firstly, acquiring a pedestrian video sequence with an identity tag, and extracting a three-dimensional spatial-temporal feature map through a backbone network; respectively extracting spatial aggregation features and time sequence difference features from the feature map; the two types of features are projected to identity and time sequence subspaces respectively, attention weighted aggregation is carried out through double memory banks, and identity enhancement features and time sequence enhancement features are generated; constructing a positive and negative sample set by adopting a similarity priority and diversity completion strategy, and calculating weighted contrast loss to jointly optimize the double-memory library; updating the memory prototype through a moving average strategy with diversity regularization; and finally, adaptively fusing the double-path enhanced features to generate discriminative feature representation, and returning to a pedestrian matching list through similarity ranking. According to the invention, through the design of the double memory libraries and the use of a plurality of dynamically combined memory prototypes to represent pedestrians, the model focuses on stable identity features irrelevant to clothes.

Disclosed is a circuit and a method for video data conversion and a display device. The circuit comprises: a pixel splicing module, to sequentially receive each group of pixel data in each frame of image data in input video data, to perform pixel splicing on the received pixel data, and to output spliced pixel data; a data conversion module, to perform data processing on the spliced pixel data to convert each frame of image data into first image data representing a first part of the corresponding frame of image and second image data representing a second part of the corresponding frame of image. The first part at least comprises a left half part of the frame of image, the second part at least comprises a right half part of the frame of image. Data throughput requirements can be met while dynamic contrast and sharpening processing is performed.

The present application relates to the field of traffic scene license plate recognition, and discloses a wide dynamic light adaptive license plate recognition method and system, which comprises the following steps: collecting a wide dynamic scene image, generating a license plate feature enhancement graph through dynamic contrast stretching and local brightness compensation, and encoding the graph into a half-edge structure graph; running a light scene adaptive switching algorithm based on the graph, constructing a five-state hidden Markov chain to calculate state posterior probability, and outputting a scene confidence vector; activating a scene-specific AI model group to generate multi-model recognition results and construct a recognition partial order set; under the constraint of the partial order set, extracting and physically checking through the upper limit to complete license plate binding and unmanned order generation; the present application solves the problems of unclear character extraction, low recognition rate and the need for manual correction in the wide dynamic light scene, improves accuracy, reduces manual cost, and ensures smooth unmanned business.

This invention relates to a visual training method for myopia prevention and control in children and adolescents, comprising: classifying individual data based on specific age groups and refractive characteristics, analyzing stimulus intensity distribution and dynamic contrast adjustment features, calculating if the visual stimulus baseline value is lower than a preset threshold, changing the pixel value change pattern to generate a first optimized image, smoothing edge features, increasing edge response intensity if the edge intensity does not meet the perceptual matching accuracy requirements to obtain a second optimized image, analyzing stimulus duration and visual feedback frequency, determining if the signal distribution is uneven, adjusting the image to generate a third optimized image, generating a visual stimulus sequence, iteratively comparing the perceptual matching accuracy of the sequence with the perceptual parameter set, determining the final suitable training image sequence, and finally outputting customized training content that reaches the neural activation threshold through activation rate calculation and response intensity mapping.

The invention relates to the field of cardiac ultrasonic examination, in particular to a transesophageal ultrasonic imaging method and system based on multi-parameter collaboration.The transesophageal ultrasonic imaging method comprises the steps that a transesophageal imaging instruction is received, a transesophageal imaging environment is confirmed based on the transesophageal imaging instruction, photo arrangement is conducted on a preliminary patient based on an ultrasonic radiography instrument and a contrast agent injection instrument, and the transesophageal imaging environment is obtained; the method comprises the following steps: setting a first atrial matrix sequence and a second atrial matrix sequence to obtain an arranged ultrasonic instrument and an arranged patient, carrying out Warner dynamic radiography on the stable patient based on preset monitoring time, a preset monitoring interval and the arranged ultrasonic instrument to obtain a dynamic radiography set, and carrying out inspection classification on the dynamic radiography set by utilizing a pre-constructed ventricle analysis model to obtain an atrial inspection result and a second atrial matrix sequence. And summarizing the atrial examination result and the microbubble shunting level to obtain an ultrasonic imaging report, and completing transesophageal ultrasonic imaging. The automation degree and accuracy of transesophageal echocardiography examination can be improved, and the diagnosis efficiency is improved.