57 results about "Flat-field correction" patented technology

The invention relates to a method for verifying a Mars sky radiance simulation result based on a Mars real-shot photo, and belongs to the technical field of Mars sky background radiance. Comprises: image acquisition; performing radiation calibration; correcting dark current; performing flat field correction; converting a radiation value; and geometric correction. The Mars sky radiance simulation method breaks through the dependence of an existing model on idealized hypothesis, performs dynamic verification by using actual shot image data, remarkably improves the authenticity and reliability of a Mars sky radiance simulation result, and effectively solves the problem of systematic deviation under a specific wave band; by constructing a complete process from image acquisition, radiation calibration, geometric modeling to brightness inversion and comparison verification, dynamic feedback and closed-loop correction of a theoretical radiation model are realized, model adaptability is improved, and fine modeling under multi-temporal and multi-meteorological conditions is supported; the method can be applied to an existing Mars rover navigation camera and an image processing link of the Mars rover navigation camera, does not need additional modification, has good engineering practicability and task compatibility, and is convenient to popularize and apply.

The invention discloses a microscopic image illumination adjustment method and system based on flat field correction, which eliminate flat field distortion caused by a camera sensor through an automatic processing flow in combination with average response of multiple images, and effectively solve the image quality problem caused by uneven illumination in combination with a background fitting method. And the reliability and subsequent analysis precision of the microscopic image are improved. According to the invention, not only is better image data provided for subsequent analysis of microscopic images, but also the microscopic imaging technology is promoted to develop towards the direction of higher automation and intelligence, and deep exploration and application in multiple fields of biomedical research, material science and the like are facilitated.

The invention discloses a detection method for fertilizer production, and relates to the technical field of fertilizer detection.The detection method comprises the following steps that a near-infrared multispectral visual detection system is installed at the working section before packaging of a fertilizer production line, the positions of a camera and an illumination source are adjusted, and multispectral images of fertilizer particles are collected; sequentially carrying out dark current correction and flat field correction on the acquired image, eliminating noise and uneven illumination, and then carrying out median filtering to remove random noise; selecting a waveband image with the best contrast ratio, separating particles from the background through threshold segmentation, and positioning each independent particle after optimizing the boundary through morphological processing; and based on the multi-band reflectivity difference, analyzing the surface material of the particles pixel by pixel, and counting the proportion of the coating area of each particle to obtain the coating coverage rate of the single particle. By introducing the near-infrared multispectral visual detection technology and the coating uniformity quantitative analysis model, non-destructive and high-precision online detection of the coating coverage rate of the fertilizer can be realized.

The invention discloses a limited angle projection phase contrast CT image reconstruction method and device based on deep learning. The method comprises the following steps: acquiring limited angle projection data of X-ray phase contrast CT scanning through an equal angle increment strategy; performing flat field correction and dark field correction preprocessing on the limited angle projection data to obtain limited angle projection data before phase recovery; preprocessing the finite angle projection data through a phase recovery strategy to obtain finite angle projection data after phase recovery; cT reconstruction is carried out on the limited angle projection data before and after phase recovery through a filtering back projection strategy, and CT images of limited angle projection before and after phase recovery are obtained; a phase contrast CT intelligent image reconstruction network model is constructed and trained; and performing reconstruction processing on the CT image of the limited angle projection before and after phase recovery through the trained phase contrast CT intelligent image reconstruction network model to obtain a reconstructed phase contrast CT image. According to the method, phase contrast CT image reconstruction can be rapidly and efficiently carried out, finite angle reconstruction artifacts can be effectively inhibited, and the image quality is improved.

Techniques for facilitating non-uniformity mitigation for imaging systems and methods are provided. In one example, a method includes cropping an image based on a defect in the image to obtain a cropped image. The method further includes cropping a supplemental flat field correction (SFFC) map based on the defect in the image to obtain a cropped SFFC map. The method further includes determining a scaling value of a scaling term based at least on a cost function. The method further includes scaling the SFFC map based on the scaling value to obtain a scaled SFFC map. Related devices and systems are also provided.

The invention provides a multi-camera curved screen Demura compensation data dynamic splicing method and system, and relates to the technical field of display, and the method comprises the steps: carrying out the flat field correction, dark current correction and dead pixel correction of a plurality of cameras, and obtaining the cameras after uniformity correction; generating a positioning map, collecting the positioning map through a plurality of corrected cameras, and calculating a sub-pixel coordinate mapping relation corresponding to each camera; dynamically estimating the curvature change of the curved screen, constructing a curved surface calibration model and generating a curved surface correction coefficient; performing brightness range correction on the curved surface correction coefficient to obtain a corrected dynamic curved surface correction coefficient; and brightness correction is carried out on gray scale images acquired by the plurality of cameras, and seamless data splicing is realized through brightness calibration among the cameras. The method effectively solves the problem of data acquisition and splicing of the large-size curved screen, is suitable for various display devices, reduces the hardware cost and the process complexity, and has high precision, flexibility and wide application prospects.

The invention discloses a display screen flat field correction method, device and system and a storage medium, which are used for improving the uniformity of a display screen image after flat field correction. Acquiring a plurality of frames of initial bright field images through acquisition equipment; performing gray average processing on the plurality of frames of initial bright field images to generate an average bright field image; selecting an ROI region on the average bright field image according to the gray level uniformity of the average bright field image; generating an ROI region mean value according to the pixel point information of the ROI region; generating a flat field correction coefficient graph according to the average bright field image and the ROI mean value; and collecting a to-be-corrected display screen through the collection device, and carrying out flat field correction processing on the collected to-be-corrected image according to the flat field correction coefficient graph.

The utility model discloses a uniform light source device for flat field correction, and belongs to the field of flat field correction. The uniform light source device comprises an area light source, a shading box, a TEC (thermoelectric cooler) arranged inside or on the surface of the area light source and used for reducing the temperature of a light-emitting part of the area light source, the illuminance sensor is arranged at any illuminance non-zero position on a non-shielding light emitting path in the shading box and is used for indirectly judging the illuminance change of a light outlet of the shading box; and the controller is connected with the TEC control circuit and the light source driver, and controls the TEC working voltage and the light source driving voltage according to the illumination change fed back by the illumination sensor so as to ensure that the illumination of the light outlet of the shading box is kept stable. Based on the structure, the controller can adjust the temperature of the area light source through the TEC so as to maintain the temperature of the area light source to be constant, the illuminance change of the light outlet of the shading box is judged according to the illuminance sensor, the driving voltage of the light source is adjusted, and the uniformity of the area light source is improved.

The invention discloses a multispectral microscope blood cell automatic classification and counting system. The system is composed of a multispectral illumination and microscopic imaging module, a spectrum and geometric calibration module, a multispectral preprocessing and cell segmentation module, a multispectral discrimination index and spectral band weight adaptive updating module, a cell graph structure classification module, a man-machine interaction module, an online adaptive learning module and the like. The method comprises the following steps: acquiring a blood smear image by a system under a narrow-band multi-spectrum condition, constructing cellular spectrum-morphological characteristics by combining a multi-scale segmentation result after noise suppression, flat field correction and background deduction, generating a discrimination index with a self-adaptive spectrum band weight, and completing joint classification and counting on a cell map; and meanwhile, carrying out constrained increment updating on the spectral band weight and the classification model by utilizing an artificial correction result of the low-confidence-coefficient cells. Compared with a traditional single-channel microscopic imaging and static classification method, the method has higher classification accuracy and counting stability under different dyeing and imaging conditions, and the workload of manual recheck can be reduced.

The invention provides a screen optical detection method and device, electronic equipment and a readable storage medium. The method comprises the following steps: shooting images of a lightened screen under XYZ three-channel optical filters by using a camera to obtain XYZ three-channel images of the screen; correcting the XYZ three-channel image, wherein the correction comprises flat field correction, four-color correction and distortion correction; synthesizing the corrected XYZ three-channel images into a color image; analyzing optical parameters of the color map; evaluating the performance of the screen based on the optical parameters. Based on the method and the device, the XYZ three-channel images of the lightened screen under the XYZ three-channel optical filter can be shot through the camera, flat-field correction, four-color correction and distortion correction are carried out on the three-channel images, and the corrected three-channel images are synthesized into the color image, so that the image seen by human eyes can be restored as much as possible, and the image quality is improved. And the optical performance of the screen can be accurately determined based on the color image.

The invention discloses a VSCEL far-field test method and device, and the method comprises the steps: providing an excitation signal for a target product, so as to enable the target product to project a laser spot to an optical screen; a distribution image of the laser spots on the optical screen is shot through an infrared camera module, a sampling image is obtained, and the shooting center of the infrared camera module is aligned with the laser emission center of the target product; preprocessing the sampling image to obtain a first intermediate image, the preprocessing including flat field correction and distortion removal processing; performing data intensity extraction on the first intermediate image to obtain energy distribution test data; determining laser divergence angle test data according to the energy distribution test data and a preset relation model; and performing image convolution and numerical operation processing on the first intermediate image to determine human eye safety test data. According to the invention, multiple test data can be obtained through the first intermediate image, multiple tests can be completed at a time, and the test efficiency can be improved.

Techniques are provided for facilitating supplemental flat field correction (SFFC) determination for infrared imaging systems and methods. In one example, a method includes capturing, by a focal plane array (FPA) of an imaging system, a first set of images of a first reference object in a scene while the first reference object is at a temperature associated with a second reference object when capturing the first set of images. The method further includes capturing, by the FPA, a second set of images of the second reference object. The method further includes determining SFFC values based on the first set of images and the second set of images. Related devices and systems are also provided.

The invention relates to a machine difference control method and a standard optical system. The method comprises the following steps: carrying out flat field correction on a camera under different working distances; shooting an object to be detected under different flat field correction conditions, selecting a plurality of feature points and measuring to obtain corresponding first feature values; measuring feature points of the same picture and the same position of the to-be-detected object, determining measurement data, and selecting a working distance with the minimum deviation as an optimal calibration distance; selecting a first camera which is qualified in calibration as a reference template, shooting the high-uniformity optical integrating sphere and extracting second characteristic values of uniformly distributed point locations; and comparing the third feature value extracted by each camera with the second feature value, and determining that the corresponding camera is calibrated to be qualified under the condition that the maximum difference value in the third feature value and the second feature value conforms to a preset specification, otherwise, performing calibration again. The method can improve the calibration precision, and effectively controls the machine difference.

The invention discloses a fruit edible rate online detection method and device based on sparse CT reconstruction. The method comprises the following steps: carrying out multi-angle sparse X-ray projection data acquisition on a fruit; carrying out dark field and flat field correction, cutting, zooming, enhancement and normalization preprocessing on the X-ray image; complementing sparse angle data by adopting an interpolation algorithm; generating a three-dimensional CT model by using a CT reconstruction algorithm; extracting a two-dimensional slice image based on axis rotation in a CT model, and extracting pulp and whole fruit areas by adopting a deep learning semantic segmentation network; and reconstructing a segmentation result into an edible rate model, and calculating the edible rate by combining the pulp density and the whole fruit mass. The detection device comprises a radiation source, an X-ray detector, a conveyor belt, an electric rotating table, a screw rod sliding table, a clamping device and the like, and supports online automatic data acquisition. The method realizes high-precision modeling of the internal structure of the fruit and automatic measurement of the edible rate, and has the advantages of high precision, high efficiency, wide adaptability and the like.

The application discloses a flat field correction method, a flat field correction system and a computer readable storage medium thereof. The flat field correction method comprises the following steps: providing a camera to be corrected and a blank wafer; collecting a dark field image of the blank wafer; collecting a bright field image of the blank wafer; and performing flat field correction calculation processing of the camera to be corrected according to the dark field image and the bright field image of the blank wafer. In the technical scheme, the blank wafer is used as a target object for flat field correction, the blank wafer is in a dust-free environment during production, is not easy to be polluted, and has extremely high consistency of wafer surface gray scale, so that the problems of difficulty in guaranteeing sufficient size and uniformity of a flat field target in the prior art can be solved.

The embodiment of the invention discloses an image flat field correction method and device and a computer readable storage medium, which are used for reducing the parameter debugging difficulty. The method comprises the steps of obtaining a calibration image and a target image; calculating a first non-uniform value of the calibration image according to the first ROI of the calibration image; calculating a second non-uniform value of the target image according to the second ROI of the target image; calculating a difference value according to the first non-uniform value and the second non-uniform value, wherein the difference value is a ratio of the second non-uniform value to the first non-uniform value; generating a target correction coefficient graph according to the difference value; and performing flat-field correction on the target image according to the target correction coefficient graph.

This invention discloses a method and system for adjusting microscopic image illumination based on flat-field correction. By automating the process and combining the average response of multiple images, this method eliminates flat-field distortion caused by camera sensors. Combined with a background fitting method, this method effectively addresses image quality issues caused by uneven illumination, improving the reliability of microscopic images and the accuracy of subsequent analysis. This invention not only provides higher-quality image data for subsequent analysis of microscopic images but also promotes the development of microscopic imaging technology towards higher levels of automation and intelligence, contributing to in-depth exploration and application in fields such as biomedical research and materials science.

A method and device for detecting filter defects of the present invention include: parallel light passing through a filter falls on the sensor of a camera; performing flat-field correction on the camera and saving the flat-field correction coefficient; changing the relative pose between the camera and the filter with respect to the parallel light so that the position where the parallel light passes through the filter and projects on the sensor changes relatively; keeping the flat-field correction coefficient of the camera unchanged and collecting pictures with different relative poses between the camera or the filter and the parallel light; preprocessing the pictures, finding the areas where the gray values change in the pictures, and obtaining the defect detection result based on the preprocessed pictures. The present invention detects defects by the change in gray values at the defect locations before and after flat-field correction, can detect defect areas that are difficult to directly see with the human eye, can detect dust that is close to the background, and is applicable to scenarios with relatively high detection accuracy.

Embodiments disclosed herein include a digital polymerase chain reaction (dPCR) operating system employing a digital image processing method for correcting illumination deviations in data associated with an array of sample plates comprising one or more arrays of sample partitions. In some embodiments, the method includes acquiring background image data corresponding to digital images acquired by the dPCR system through a camera after a background cycle of dPCR detection. For each partition, a local flat field correction coefficient is derived and applied to the background image data to obtain local offset corrected background image data. A global flat field correction coefficient set is then determined using the local-bias-corrected background data. And performing illumination deviation correction on the end point image data by jointly using local and global flat field correction coefficients to generate a deviation-corrected end point illumination value.

The application provides a kind of flat field correction parameter acquisition method and system of image sensor chip, it is related to image processing technical field, comprising: the gray value of the picture currently collected by image sensor chip is adjusted to within the preset bright field target gray value range, then in the preset erasing time range current erasing time is selected, and the dark field picture is obtained by erasing image sensor chip according to current erasing time;The gray value after erasing of dark field picture is obtained, and when the gray value after erasing is within the preset dark field target gray value range, the corresponding current erasing time and dark field picture are saved as dark field parameter;Otherwise, according to current erasing time, the preset erasing time range is reduced, and current erasing time is selected again.The beneficial effect is that the dark field parameter of image sensor chip can be automatically and quickly acquired, without manual intervention, effectively saving the time and labor cost of flat field correction, and solving the annoyance caused by the tedious flat field correction process for engineers.

The invention discloses a single-pixel imaging semiconductor wafer surface defect extraction method and system, and relates to the technical field of wafer defect extraction, and the method comprises the steps: carrying out the dark current deduction and brightness flat field correction of a defect-free wafer bright field image, generating a reference mask, dividing tiles, and building coordinate mapping; generating a defect sensitive pattern pair, performing tile-by-tile projection, performing integral acquisition by using a single-pixel detector, and performing complementary difference to obtain a phase shift difference group; in-phase and orthogonal components are obtained through four-step phase shift phase locking demodulation, defect global coordinates are estimated according to the phase and frequency slope, and a frequency domain suppression weight is constructed through a defect-free image Fourier spectrum to obtain saliency; and the defect type is judged through self-adaptive adjustment of the distance between the emitting end and the tile and saliency secondary difference. According to the method, the in-phase / orthogonal component and amplitude-phase distribution are directly solved by adopting the four-step phase shift method, the defect coordinates are solved by using the phase-frequency slope, image reconstruction is avoided, the calculation overhead is reduced, and the positioning precision is improved.

The invention discloses a streak camera image flat field correction system and method based on a pulse time-varying light source under a working scanning speed, and solves the problems of inaccurate response uniformity and high realization difficulty of an image flat field corrected by an existing method. The device specifically comprises a signal source, a pulse time-varying light source, a monitoring photoelectric detector, an oscilloscope and a series of attenuation slices with different transmittances, an A output channel of the signal source is connected with the pulse time-varying light source, a B output channel of the signal source is connected with the streak camera, and a C output channel of the signal source is connected with a first input end of the oscilloscope; the emergent end of the pulse time-varying light source corresponds to the incident end of the streak camera; the detection end of the monitoring photoelectric detector corresponds to the pulse light emitted by the pulse time-varying light source, and the output end of the monitoring photoelectric detector is connected with the second input end of the oscilloscope; a series of attenuation slices with different transmittances are used for being arranged at the emergent end of the pulse time-varying light source in a switching mode so as to attenuate the intensity of emergent pulse light of the pulse time-varying light source to different degrees.

The application discloses a kind of edge camera's flat field correction method and device in multi-camera vision detection, which comprises: real-time acquisition of the image in the field of view of edge camera, identify and locate the edge profile of product in image, according to the range of product in field of view, the field of view is divided into product part and productless part;Based on the first correction coefficient of product part calculated by conventional flat field correction method, based on the first correction coefficient, according to the proportion of product part in field of view, the correction coefficient of productless part is calculated;The correction coefficient at the junction of adjacent area is smoothed, and the final flat field correction coefficient of each pixel in the entire field of view of edge camera is obtained, and the final flat field correction coefficient is applied to edge camera image acquisition, and flat field correction is completed.The scheme can improve the flat field correction effect and stability of edge camera.

Techniques are provided for facilitating supplemental flat field correction (SFFC) determination for infrared imaging systems and methods. In one example, a method includes capturing, by a focal plane array (FPA) of an imaging system, a first set of images of a first reference object in a scene while the first reference object is at a temperature associated with a second reference object when capturing the first set of images. The method further includes capturing, by the FPA, a second set of images of the second reference object. The method further includes determining SFFC values based on the first set of images and the second set of images. Related devices and systems are also provided.

The application discloses a deep learning-based limited-angle projection phase contrast CT image reconstruction method and device, which comprises the following steps: acquiring limited-angle projection data of X-ray phase contrast CT scanning through an equal-angle increment strategy; performing flat-field correction and dark-field correction preprocessing on the limited-angle projection data to obtain limited-angle projection data before phase recovery; performing preprocessing on the limited-angle projection data through a phase recovery strategy to obtain limited-angle projection data after phase recovery; performing CT reconstruction on the limited-angle projection data before and after phase recovery through a filtered back projection strategy to obtain CT images of the limited-angle projection before and after phase recovery; constructing a phase contrast CT intelligent image reconstruction network model and training; and performing reconstruction processing on the CT images of the limited-angle projection before and after phase recovery through the trained phase contrast CT intelligent image reconstruction network model to obtain reconstructed phase contrast CT images. The application can quickly and efficiently perform phase contrast CT image reconstruction, effectively suppress limited-angle reconstruction artifacts and improve image quality.

The invention discloses a halo prediction-based microscopic image shadow removal method, computer equipment, a storage medium and a program product. The objective of the invention is to solve the problem that flat-field correction needs multiple groups of flat-field correction in a zoom microscope, and to solve the problem that flat-field correction fails when exposure time is prolonged or shortened. According to the method, flat field correction does not need to be carried out on the image in advance, and the influence caused by texture introduction of the used white board in the flat field correction process is reduced. In addition, according to the collected image, the halo map is predicted in real time through the model, brightness compensation is carried out on the image according to the halo map, and the compensation effect is better.

Techniques are provided for assembling a flat field map suitable for performing flat field correction without the use of a physical shutter. In one example, a method includes receiving an image frame comprising a plurality of pixels. The image frame is captured by an array of image sensors of an imaging system in response to radiation received from a scene external to the imaging system. The image frame comprises a plurality of subsets of the pixels. The method also includes determining, for each subset, whether content associated with the scene is contained in the subset; aggregating the subsets determined to not contain the content into a flat field map. The method also includes performing a non-uniformity correction using the flat field map to determine a plurality of correction terms to correct for non-uniformities associated with the image sensors. Additional methods and systems are also provided.

Techniques are provided for facilitating supplemental flat field correction (SFFC) determination for infrared imaging systems and methods. In one example, a method includes capturing, by a focal plane array (FPA) of an imaging system, a first set of images of a first reference object in a scene while the first reference object is at a temperature associated with a second reference object when capturing the first set of images. The method further includes capturing, by the FPA, a second set of images of the second reference object. The method further includes determining SFFC values based on the first set of images and the second set of images. Related devices and systems are also provided.

The present disclosure provides a flat field correction method and device, electronic equipment and storage medium, and relates to the field of image processing, which comprises: acquiring multiple background pictures of different positions of an object to be detected; calculating first, second and third gray values of the multiple background pictures; generating a target background template image of the object to be detected according to the gray values of the multiple background pictures, the first, second and third gray values of each pixel point; and correcting an object to be detected image according to the target background template image. The method of the present disclosure does not need to guarantee the absolute blank state which is difficult to achieve when obtaining the correction template in the past, and the background template image is generated one by one according to the background pictures of the object to be detected, so that the noise reduction template is more targeted, and the quality of image noise reduction is improved.