21 results about "Maximum Pixel" patented technology

The embodiment of the invention provides a pleural effusion grading model training method, a pleural effusion grading method and electronic equipment, and relates to the technical field of image processing. The method comprises the following steps: acquiring a pleural effusion ultrasonic image, inputting the pleural effusion ultrasonic image into a pre-trained pleural effusion grading model to obtain an effusion binary mask, performing template matching on the pleural effusion ultrasonic image, identifying at least two reference scale marks with a known physical distance marked on a scale in the image, and determining the pleural effusion grading model according to the identified reference scale marks. Determining the pixel coordinates of each reference scale in the image, performing connected domain analysis on the binary mask, extracting a connected domain with the maximum longitudinal extension length as a target effusion region, calculating the maximum pixel length of the target effusion region in the longitudinal axis direction of the image, and determining the target effusion region according to the physical spacing, the two pixel coordinates and the maximum pixel length. The physical depth of the pleural effusion is calculated, and clinical grading is conducted. Therefore, evaluation from the pleural ultrasound image to the physical depth of the effusion can be realized.

The invention provides a display method and electronic equipment, and is applied to the technical field of display driving. The display method comprises the steps of determining a target display scene; determining a target refresh rate and a target pixel turn-on voltage corresponding to the target display scene; wherein the target refresh rate limits the maximum pixel charging duration of the target display scene, the target pixel turn-on voltage is in negative correlation with the maximum pixel charging duration, and the display device is controlled to display the target scene at the target refresh rate and the target pixel turn-on voltage so as to reduce the display power consumption of the display device.

The present invention relates to an integrated circuit of an image capture device for automatically optimizing the ratio (A1 / A0) of the output image area (A1) to the main window area (A0), and for optimizing (preferably maximizing) the product D1×A1 of the output pixel density (D1) multiplied by the output image area (A1) of the motion detection area that defines an output image (P1) consisting of a predetermined maximum number (N1m) of pixels. The integrated circuit includes an array light sensor for capturing an input image (P0) and a processing unit configured to perform the following actions: - in an image detection mode, a series of consecutive reference images (Prefj) are captured at different times by a subarray of Nr reference light sensors, and a number (Nm) of motion pixels (pm) whose value difference between the two reference images exceeds a predetermined threshold deviation for detecting motion within an area of ​​the reference image is determined, and then switching; - in an image capture mode, the parameters of the captured output image are defined as follows: ● an output window (W1) with an output window area (A1) surrounding at least a predetermined number (Nmt) of the motion pixels (pm), and ● an output pixel density D1 = N1 / A1 ≦ DO, where N1 ≦ N1m; ● capturing an output image (P1) defined by the output window (W1) having the output window area (A1) and the output pixel density (D1) and transferring the output image (P1) including N1 pixels from the integrated circuit.

The invention provides an image detection segmentation method and device for image small target clustering. The method comprises the following steps: receiving a multi-resolution original image; converting the original image into a grey-scale map, and obtaining adaptive parameters based on the mean value of the grey-scale map, the maximum pixel value of the grey-scale map and the image brightness intermediate value; performing gamma correction on the original image based on the adaptive parameter to remove an image shadow to obtain a corrected image; performing target detection and segmentation on the corrected image based on a detection segmentation model to obtain the category of a target; under the condition that the target is a small target, clustering the small target by adopting a density clustering algorithm to obtain a clustering result; wherein the small target is a target of which the target size is smaller than a preset size; and outputting the category, confidence and target contour area coordinate points of the small target based on a clustering result. The method can solve the problems that the detection and segmentation algorithm in the prior art is poor in detection and segmentation effect on the shadow part of the image, and messy is generated due to excessive small target segmentation.

The invention discloses a gas leakage detection method and system based on laser speckle imaging, and the method comprises the steps: irradiating the outer wall surface of a to-be-monitored region with laser beam expansion to form laser speckles, and continuously collecting a plurality of monitoring speckle images of the to-be-monitored region; segmenting the monitored speckle image and the corresponding original speckle image without leakage into a plurality of sub-windows, and calculating the frequency spectrum amplitude and the frequency spectrum phase of each sub-window; calculating a correlation coefficient between the two sub-windows according to the spectrum amplitudes and the spectrum phases of the sub-windows corresponding to the original speckle image and the monitoring speckle image; marking the sub-windows in the monitoring speckle image corresponding to all the correlation coefficients smaller than a preset threshold value as gas leakage coarse positioning areas; and for each pixel point in the leakage coarse positioning area, calculating a pixel-level imaging operator of the pixel point, and taking the pixel point corresponding to the maximum pixel-level imaging operator as a gas leakage point.

The invention discloses a display image uniformity statistical method and device and a storage medium, which are used for improving the accuracy of gray uniformity analysis of images shot by a display. Generating a row / column direction minimum bounding rectangular frame for the normalized image; performing intersection processing and connected domain separation processing according to the minimum bounding rectangular frame in the row / column direction, and calculating a gray statistical information value of a separation region; generating a blank image, replacing the gray value of the blank image with the gray statistical information value, and generating a row curved surface image and a column curved surface image; circulating the array of the blank images, generating a dynamic row and column coordinate array of a neighborhood, and generating a vector field image; performing algorithm remapping processing on the normalized image and the vector field image to generate a result image; combining the result images, and filling the maximum pixel value of the multi-channel image into the to-be-processed image to generate the to-be-processed image; and generating a target filling image, and carrying out gray level distribution uniformity analysis according to the gray level value data.

To mitigate some problems of pixel color mapping used in SLHDR type of HDR video decoding, we teach a high dynamic range video encoding circuit (300) configured to encode a high dynamic range image (IM HDR) having a first maximum pixel luminance (PB CI) with a second image (Im LWRDR) having a lower dynamic range and a corresponding lower second maximum pixel luminance (PB C2), the second image being functionally encoded as a luminance mapping function (400) for a decoder to apply to pixel luminances (Y PQ) of the high dynamic range image to obtain corresponding pixel luminances (PO) of the second image, the encoder comprising a data formatter (304) configured to output the high dynamic range image and metadata (MET) encoding the luminance mapping function (400) to a video communication medium (399), the functional encoding of the second image being further based on a color lookup table (CL(Y PQ)) encoding a multiplier constant (B) for all possible values of pixel luminances of the high dynamic range image, and the formatter being configured to output this color lookup table in the metadata, characterized in that the high dynamic range video encoding circuit comprises a gain determination circuit (302) configured to determine luminance gain values (G PQ) quantifying a ratio of output image luminances equal to a luminance position of a correct normalized luminance position divided by output luminances of luminances of pixels of the high dynamic range image, wherein the high dynamic range video encoding circuit comprises a color lookup table determination circuit (303) configured to determine the color lookup table (CL(Y PQ)) based on values of the luminance gain values for various luminances of pixels present in the high dynamic range image. Similarly, we teach how to embody the same principles in a SLHDR type of video decoder.

The application provides a personnel access detection method and device, equipment and a storage medium, and relates to the technical field of digital signal processing. The method comprises the following steps: obtaining a real-time foreground image by subtracting a background image from a real-time temperature image and performing denoising processing on the real-time foreground image; screening pixel points according to a temperature threshold, dividing a plurality of preselected frames in the real-time foreground image, and adjusting the position of the preselected frame by taking the pixel point with the maximum pixel value in the frame as a new center point; screening a plurality of target preselected frames by using preselected frame scores, matching the target preselected frames with each historical trajectory, and generating the latest trajectory of each personnel target; calculating the moving direction of the personnel target according to the current position and displacement step in the latest trajectory; and statistically obtaining the number of personnel access according to the moving direction. The image processing flow of the above scheme is simple in logic and small in calculation amount, meets the low-power consumption requirement, the tracking and statistical flow divides multiple targets by using preselected frames, is strong in generalization and is not prone to missing detection, and the detection effect is stable.

A 3D reconstruction method, a confocal microscopy system, and a computer program product are disclosed. The confocal microscopy system includes a spatial light modulator, an imaging unit, and a displacement platform. The spatial light modulator can project M different projection patterns with a preset phase shift relationship. The M projection patterns, when superimposed, can cover the entire projection field of view, where M is a positive integer greater than 1. The 3D reconstruction method includes controlling the displacement platform to move the object under test along a preset direction. At each displacement position, the spatial light modulator projects onto the object under test. After each projection, the imaging unit acquires a projected image of the object's surface. A composite image is generated based on the M projected images acquired in each projection cycle. 3D reconstruction is performed based on the maximum pixel value at the same pixel position in all composite images to obtain the 3D reconstruction result. This addresses the technical problem that traditional confocal techniques are difficult to adapt to the needs of efficient and real-time measurement.

This invention provides a method and system for automatically removing bed slabs from CT images, relating to the field of image segmentation technology. The method includes: acquiring the three-dimensional dimensions X, Y, and Z of the CT image; constructing a 2D image of size X and Y; traversing pixel values ​​along the z-axis of the CT image and assigning the maximum pixel value at (x, y) to (x, y) in the 2D image; performing threshold segmentation on the 2D image based on the CT values ​​to extract the bed slab and human tissue regions, obtaining a binary image; performing seed point region growing processing on the binary image to extract the human tissue regions, obtaining a mask_2D image; stitching together Z mask_2D images along the z-axis of the CT image to obtain a mask_3D image; and performing image template segmentation on the CT image based on the mask_3D image to obtain a 3D image after removing the bed slab. This invention achieves automatic and rapid removal of bed slabs from CT images through image segmentation technology.

The application relates to a target object positioning method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: obtaining a target image through a target camera installed on a target vehicle; obtaining a pixel mask of a target object through an identification model; performing lane line identification on the target image through a lane line detection model to obtain a lane line function corresponding to each lane line; inputting a target pixel longitudinal coordinate of the pixel mask of the target object into the lane line function to obtain a predicted transverse coordinate; determining a first lane line and a second lane line according to each predicted transverse coordinate, a minimum pixel transverse coordinate and a maximum pixel transverse coordinate, and determining a lane in which the target object is located; and determining position information of the target object according to a distance between the target object and the target vehicle and the lane in which the target object is located. The method can improve the positioning speed of the target object.

A three-dimensional reconstruction method, apparatus, and microscopic reconstruction system based on multidimensional modulation are disclosed. The microscopic reconstruction system includes a projection unit, an imaging unit, and a motion unit. The three-dimensional reconstruction method includes controlling the motion unit to drive the sample under test to move relative to the imaging unit along a preset direction; at each displacement position, controlling the projection unit to project complementary illumination patterns and / or illumination patterns with different spatial scales onto the sample under test; after each projection, controlling the imaging unit to acquire a projected image of the sample surface; generating a sharpness map based on the projected images acquired in each projection cycle; wherein, one projection of complementary illumination patterns or illumination patterns with different spatial scales constitutes one projection cycle; and performing three-dimensional reconstruction based on the maximum pixel value at the same pixel position in all sharpness maps to obtain the three-dimensional reconstruction result of the sample under test. A three-dimensional reconstruction method that can achieve high accuracy and stability under complex sample conditions is proposed.

A processing system and method for compressing image data divides an image into pixel blocks. For each block, it computes minimum and maximum pixel values, determines bits needed to store pixel-to-minimum differences, calculates those differences, and stores them as bit-planes in memory. The system can store minimum / maximum values in metadata and compute absolute differences between them. Bit requirements are calculated using log 2(delta+1) rounded up. Bit-planes may be compressed for streaming access or fixed-size allocated for random access. The approach enables bandwidth reduction while maintaining random access or storage reduction with streaming access. This novel technique provides efficient image compression with flexible access options.

An example laser beam scanning projection system, a method for modulating an optical output of a laser beam scanning projection system, and a head-worn display are provided. The example laser beam scanning projection system includes an optical engine, a scanning system, and a controller. The optical engine generates an optical output corresponding to a pixel location in a display image. The scanning system projects the optical output to the pixel location on a display surface displaying the display image. The controller determines a minimum pixel brightness associated with the display image, and a maximum pixel brightness. The controller further determines a modulated region of the display image based on the maximum pixel brightness. The controller adjusts an optical output brightness of the optical output such that a pixel brightness at the pixel location is at the maximum pixel brightness for pixel locations in the modulated region.

Methods, apparatuses and computer program products for enhancing accuracy in image processing and analytics are provided. For example, an example method includes receiving an image data object and a target object maximum pixel size parameter associated with a target object; generating a plurality of pixel chunks based at least in part on the image data object and the target object maximum pixel size parameter; generating a plurality of predicted individual target object counts based at least in part on parallel processing of the plurality of pixel chunks; and generating a predicted total target object count associated with the target object based at least in part on the plurality of predicted individual target object counts.

A decoding device includes a transformer sets a decoded luminance component of a prediction target block to the same number of samples as that of the chrominance component corresponding to the decoded luminance component of the prediction target block and generates a luminance reference signal. A specificator specifies luminance pixels having minimum and maximum pixel values of the decoded luminance component adjacent to the decoded luminance component of the prediction target block, respectively, outputs luminance pixel values obtained from specified luminance pixels, and outputs chrominance pixel values from pigment pixels corresponding to the luminance pixels. A derivator derives a linear prediction parameter from the two pixel values and a linear prediction model. A chrominance linear predictor obtains chrominance prediction signal applying the linear prediction model based on the linear prediction parameter to the luminance reference signal. The chrominance prediction and residual signals are summed to generate a reconstructed chrominance signal.

The present application relates to the technical field of image processing, and provides a kind of based on multiscale prior injection image rain removal method and system, method includes the gray scale image formed by the maximum pixel value and minimum pixel value of rain day image along channel dimension is subtracted;Through the residual branch of pre-trained U-Net network, the multiscale latent background prior feature of initial rough rain-free image is extracted;Under the guidance of multiscale latent background prior feature, the multiscale rain stripe feature of rain day image is extracted by PITformer branch, and the first scale decoder rain stripe feature is obtained;After again passing through Tformer module and convolution module, it is added with rain day image, and rain removal image is obtained.The present application adopts U-Net network, guides network to generate rain-free image with rich texture details by introducing prior information in each scale layer, realizes accurate image recovery, and improves rain removal performance.

Embodiments of the present disclosure relate to brightness enhancement for a laser beam scanning projection system. An example laser beam scanning projection system, a method for modulating an optical output of a laser beam scanning projection system, and a head mounted display are provided. The example laser beam scanning projection system includes an optical engine, a scanning system, and a controller. The optical engine generates optical outputs corresponding to pixel locations in the display image. The scanning system projects an optical output to pixel locations on a display surface that displays a display image. The controller determines a minimum pixel luminance associated with the display image, and a maximum pixel luminance. The controller also determines a modulation region of the display image based on the maximum pixel brightness. The controller adjusts an optical output brightness of the optical output such that a pixel brightness at the pixel position is at a maximum pixel brightness for the pixel position in the modulation region.

The application discloses a display image uniformity statistical method, device and storage medium, which is used for improving the accuracy of the gray uniformity analysis of the display photographed image. A row / column direction minimum circumscribed rectangle frame is generated for the normalized image; intersection processing and connected domain separation processing are performed according to the row / column direction minimum circumscribed rectangle frame, the gray statistical information value of the separated area is calculated; a blank image is generated, the gray value of the blank image is replaced by the gray statistical information value, and a row surface image and a column surface image are generated; the array of the blank image is cycled, the dynamic row and column coordinate array of the neighborhood is generated, and a vector field image is generated; the normalized image and the vector field image are subjected to algorithm remapping processing, and a result image is generated; the result image is merged, the maximum pixel value of the multi-channel image is filled into the image to be processed, and the image to be processed is generated; and a target filling image is generated, and the gray distribution uniformity analysis is performed according to the gray value data.

The application discloses a lens correction data detection method, extracts effective correction data in the lens correction data, divides the effective correction data into N pieces of correction data, wherein N is a multiple of 4; groups the N pieces of correction data to obtain M groups of data, wherein M is an integer greater than 1, each group of data in the M groups of data includes multiple pieces of correction data; if the increase / decrease parameter of each piece of correction data meets the set increase / decrease condition, the coordinate value of the maximum pixel of each group of data meets the set coordinate condition, and the maximum pixel value and the minimum pixel value meet the set pixel value condition, it is determined that the lens correction data meets the correction requirement. The lens correction data detection method, device, electronic equipment and medium disclosed by the application can effectively improve the detection efficiency of the correction data of the camera module.

The application discloses a high-altitude overflight scene motion small target detection method and device, including the following steps: A: constructing a to-be-recognized image sequence set; B: constructing a visual perception module, and constructing a smooth feature map sequence; C: constructing a change perception module, and obtaining a first space-time dynamic feature map corresponding to an intermediate frame in the smooth feature map sequence; D: constructing a motion information calculation module, and obtaining an optimized second space-time dynamic feature map after motion energy calculation, receptive field enlargement, motion target scale screening and background suppression; E: constructing a receptive field enlargement module, and obtaining a third space-time dynamic feature map; F: respectively obtaining corresponding third space-time dynamic feature maps, and taking the position of the maximum pixel point value in the third space-time dynamic feature map as the position of the motion small target. The application can effectively distinguish the background environment and the small target in the image, detect the position of the motion small target in the background environment, and improve the motion small target detection efficiency.