71 results about "Flat-field correction" patented technology

By rendering a special test image and applying flat-field correction for a device under test (DUT) non-uniformity, the E-O response of a reflective LCOS microdisplay can be quickly determined through an image processing algorithm. The measurement is made in a spatial domain instead of in a temporal domain. From the measurement, the driving voltage of maximum brightness, Vbright, can be determined. The use of Vbright enhances the visibility of pixel and sub-pixel defects to the test system. Other defect visibility enhancements are achieved through appropriate sampling rate, optical axis rotation and improved parallelism between the DUT and the CCD sensor camera. By modeling a sub-pixel defect as a local non-uniformity, a near neighborhood algorithm may be used for detection. The neighborhood algorithm does not rely on the alignment between the display pixels and the camera pixels.

The embodiment of the invention discloses a relative radiometric calibration method for light field camera, which comprises the steps of: carrying out calibration processing of images emitted from an uniform area light source by a light field camera to obtain measurement values of dark current noise, grey centroid coordinates of subimages of microlens, and flat-field correction coefficients; and processing other original light field images shot by the light field camera correspondingly by utilizing the measurement values of dark current noise, the grey centroid coordinates of subimages of microlens, and the flat field correction coefficients to obtain light filed images after relative radiometric calibration processing. The method of the invention can eliminate dark current noise in light field camera system, remove invalid pixels between subimages of microlens, and correct the problem of pixel response nonuniformity caused by various factors, thereby improving the performance of the light field camera.

Methods, apparatuses, and systems for imaging biological / chemical samples are provided. A calibrated imaging system can allow a user to obtain an optimal focus setting (position) for any effective distance (e.g. a zoom setting). The optimal focus can be determined from a functional approximation that defines a relationship between effective distance and focus setting. A user can input a size, and an imaging system can determine the appropriate effective distance and focus. An imaging system can also determine a size based on any effective distance. A flat-field correction can also be determined for any effective distance or size.

The invention discloses a method for correcting response inconsistency of linear array CCD (Charge Coupled Device) image elements. According to the characteristics of a CCD, the existing two-point flat field correction method is improved based on correct calculation of dark current noise; and based on formation mechanism of response inconsistency of the image elements, an inconsistency correctionmethod is divided into two independent parts (dark current noise and inconsistency correction and photoelectric response inconsistency correction), and digital gain correction is also introduced, finally, the correction of response inconsistency of the linear array CCD image elements is implemented. The method provided by the invention can be used for overcoming the defect that, in a two-point correction method, values of dark image elements cannot correctly reflect present dark current noise when the CCD is partially saturated; and the method can be widely used in the present imaging devices, has the characteristics of being easy to realize and high in precision, and can be used for eliminating image degradation caused by dark current noise and image element response inconsistency noise and improving the imaging performance of a detector.

A fluorescence reference plate for a fluorescence spectroscopic instrument is arranged with fluorescent layers having different excitation and emission characteristics. The fluorescent layers are ordered in the form of a stack for providing a flat-field calibration standard over multiple bands of wavelengths.

The invention relates to a flat field method for an imaging interferometer. The optical axis of the flat field imaging interferometer is collimated to the center of the opening of the flat field light source, the interferometry image data output by the flat field imaging interferometer is acquired by an image acquisition card, and sent to the computer to processing, the flat field correction matrix is calculated, the flat field uncertainty is analyzed, and the flat field correction matrix is acquired. The invention solves the technical problem that the allsidedness and the effect of the correction are correspondingly poor in the technical background. The invention is mainly utilized on the flat field of an entire spatial modulation imaging interferometer to eliminate the system error, and the inconsistence of the response between pixels can be corrected at one-time. The invention is also suitable for the flat field of the imaging interferometer embarked on a plane or a satellite during the flying processing by utilizing the ground standard radiation field.

An inspection tool includes a camera for obtaining images of a wafer and a controller configured for performing light source flat field correction, optical image warping correction, and optical image scale correction of the images. In operation, separate inspection tools are calibrated separately to obtain a characteristic response with respect to imaging and / or illumination for each such inspection tool. A standard target is then imaged by each inspection tool and the response of each of the inspection tools is normalized to ensure uniformity of the output of each inspection tool with respect to the other inspection tools.

Various techniques are disclosed for performing non-uniformity correction (NUC) for infrared imaging devices. Intentionally blurred image frames may be obtained and processed to correct for FPN (e.g., random spatially uncorrelated FPN in one embodiment) associated with infrared sensors of the infrared imaging device. Intentionally blurred image frames may be used to distinguish between FPN associated with the infrared sensors and desired scene information. Advantageously, such techniques may be implemented without requiring the use of a shutter to perform flat field correction for the infrared imaging device.

The invention discloses a flat field correction method for area array camera imaging. The method comprises the following steps: a, obtaining a bright image (white) and a dark image (black) of a uniform sample; b, calculating fixed mode noise and photoresponse nonuniformity of the camera sensor; c, obtaining the nonuniformity of illumination imaging according to an actual imaging sample and the environment; and d, calculating coefficients of flat field correction, and correcting the collected image. By adoption of the method provided by the invention, the uniform sample does not need to be frequently used for performing the flat field correction, the sample easy to obtain can be selected according to the onsite condition to obtain the nonuniformity of illumination imaging, and meanwhile the fixed mode noise and photoresponse nonuniformity of the camera sensor are obtained in combination with the pre-obtained white image and the black image, therefore the flat field correction coefficient of the camera can be obtained conveniently and quickly.

The optical imaging of two-dimensional solute zone arrays in electrophoresis gels is corrected for nonuniformities in the optical system such as those arising from the light source or from light dispersion underneath the gel. The correction is achieved by the use of a reference plate that responds to a light source uniformly along its length and width by being either uniformly light absorptive or uniformly light transmissive, or by emitting light upon excitation. Thus, any nonuniformities or deviations in the image of the reference plate arise only from nonuniformities or deviations within the optical system. Analogous corrections are made in other two-dimensional assay images, such as microarrays and microtiter plates.

The embodiment of the invention provides a flat-field correction method, a flat-field correction device, an image verification method and an image verification device. According to the flat-field correction method, a dark-field image is obtained by adjustment of the exposure time and a gained camera; the incorrect operation due to artificial lens covering is avoided; therefore, the quality of thedark-field image is improved; simultaneously, the operation quantity is reduced through a manner of obtaining the dark-field image by adjusting camera parameters; and thus, the acquisition efficiencyof the dark-field image is effectively increased. By means of the flat-field correction method, average filtering of gray values of various pixel points in an alternate bright-field image is carried out; a high-frequency component is removed by filtration; therefore, quality damage of the alternate bright-field image due to the special situations of fine grains on a white reference, uneven texture, dust on a glass sheet and the like can be reduced; and thus, the quality of the bright-field image is effectively improved. According to the embodiment of the invention, the flat-field correction precision is improved by improving the quality of the dark-field image and the bright-field image; simultaneously, the condition that the dark-field image is obtained by artificial operation is avoided;and the acquisition efficiency of the dark-field image is obtained.

The present invention discloses a flat-field correction method based on line-scan digital camera scanning. The method is applied to a line-scan digital camera and comprises the following steps of S1 obtaining a preview image of a pathological section, focusing the line-scan digital camera according to the preview image, and obtaining a Z-axis focal length position of the line-scan digital camera; S2 using the line-scan digital camera to scan the pathological section by taking the Z-axis focal length position as reference to obtain a pathological section image; S3 separating the pathological section image into three grey-scale maps according to red, green and blue three color channels, and calculating to obtain the correction coefficient curves of the colors respectively according to the three grey-scale maps, and carrying out the flat-field correction on the image scanned by the line-scan digital camera according to the correction coefficient curves of the three colors. The flat-field correction method based on the line-scan digital camera scanning of the present invention can filter the interference of the dust, the impurity and the own noise of the line-scan digital camera, and achieves the purpose of improving the flat-field correction accuracy.

The invention discloses a camera calibration and flat field correction device, a camera calibration method and a flat field correction method. The camera calibration and flat field correction device comprises a camera obscura; a light source generator which comprises an LED light source and an optical fiber connected with the LED light source; A reference camera; and a Mobile station. The camera calibration and flat field correction device adopts an LED light source with adjustable brightness as an emission light source; the reference camera is used as a detector of illumination light irradiance; the camera to be detected and the reference camera are mounted on a movable moving table; The device can adjust the irradiance of illumination light by adjusting the brightness of the LED light source or adjusting the distance between the camera to be detected and the reference camera and the LED light source. wherein the reference camera is an area array detector and can also be used for detecting the irradiation uniformity of illumination light, so that the device is composed of cheap components and can carry out rapid and accurate camera calibration and flat field correction.

The invention discloses a lensless holographic microscopic phase recovery method with multi-constraint information and a device thereof. The method comprises the following steps: step S1 of turning off a light source, and collecting a dark field image by using a lensless holographic microscopic device; step S2 of turning on the light source to collect a bright field image under uniform illumination of the light source; step S3 of placing a sample above an image sensor to ensure that the distance between the sample and the image sensor is much smaller than that between the sample and the lightsource; turning on the light source to collect a holographic image sequence; step S4 of performing flat field correction on any holographic image needing to be calculated; step S5 of performing an autofocus algorithm on the image subjected to flat field correction, and finding the position of the sample in space; and step S6 of using a phase recovery algorithm with multi-constraint information forthe autofocus image having undergone automatic focusing, to reconstruct the accurate amplitude and phase information of the sample. According to the method and device, the accurate phase informationcan be recovered from the captured holographic image without increasing the complexity of a system and the number of images acquired.

A correction information generation method and a correction information generation apparatus enabling easy Flat-Field Correction operation without special accessory equipment are provided. The correction information generation method for performing Flat-Field Correction of X-ray detection sensitivity on a pixel detector, includes the steps of: moving the relative position of a detector 130 with respect to an incident X-ray having a cross-sectional beam shape traversing a detection surface so that the whole of the detection surface is irradiated with the incident X-ray in total time and each of pixels arranged in the moving direction is uniformly irradiated; and generating information for correcting the sensitivity of a pixel based on an intensity value detected for a given energy band of the incident X-ray.

The invention relates to a method for correcting a flat field of two-dimensional optical detection. A first optical filter is arranged between a CCD (Charge Coupled Device) and at least one reference illuminator. The reference illuminator is moved relative to the CCD, so as to utilize the CCD to capture a plurality of individual images and integrate a flat field message. Accordingly, a first light intensity correcting field profile is calculated, thereby obtaining a first light intensity correcting rate corresponding to each image coordinate in an image coordinate system of CCD. After a deviated projecting detection image of at least one to-be-detected illuminator is captured by the CCD, a corrected light intensity value corresponding to each image coordinate in the deviated projecting detection image is calculated according to the first light intensity correcting rate, so as to obtain a light intensity correcting detection image.

The invention discloses a lens-free holographic microscopic particle characterization method based on a convolutional neural network. The method comprises the following steps: S1, firstly, acquiring adark field image, then, acquiring a bright field image uniformly illuminated by a light source; S3, placing a sample above a sensor, acquiring microscopic images of the sample of different refractiveindexes, and marking corresponding refractive index of each image; S3, performing flat-field correction for all the holographic microscopic images; SS4, calculating a center of all particles in the images, and cutting images of each particle; S5, cleaning all the cut images, randomly dividing the images into a training set, a verification set and a test set; taking the training set as input of the convolutional neural network, training a classification network, verifying an effect training parameter on the verification set, finally, testing a classification effect on the test set, wherein a classification label corresponding to the particle is a refractive index characterization result of the particle. The method provided by the invention can perform quick, convenient and accurate characterization for biological samples under a large field of view.

The invention discloses a matrix decomposition-based lensless holographic microscopic speckle noise removing method and a matrix decomposition-based lensless holographic microscopic speckle noise removing device. The matrix decomposition-based lensless holographic microscopic speckle noise removing method comprises the following steps: S1, turning off a light source, and acquiring a dark field image; S2, turning on the light source, and acquiring a bright field image under uniform irradiation of the light source; S3, placing a particle-containing solution sample above a sensor, guaranteeing that the distance from the sample to the sensor is much smaller than the distance from the sample to the light source, turning on the light source, and acquiring a holographic image sequence of the sample; S4, performing flat field correction on any hologram image required to be calculated; S5, performing noise separation on the corrected holographic image by a matrix decomposition algorithm, and decomposing the corrected holographic image into two parts, namely a particle hologram part and a background noise part; S6, further performing image analysis and processing on the calculated holographic image. Through the matrix decomposition-based lensless holographic microscopic speckle noise removing method and the matrix decomposition-based lensless holographic microscopic speckle noise removing device, the speckle noise as well as interference fringe noise generated by multiple reflections of the sample can be removed, so that high-precision dynamic 3D imaging is achieved.

The invention discloses a flat field correction method of a linear array camera suitable for field working conditions. The method includes: obtaining an original correction coefficient matrix by shooting an initial gray value matrix of an initial row of a screen to be inspected; obtaining an original gray value matrix by scanning and photographing the gray value image of the screen to be inspectedby the linear array camera; multiplying the original gray value matrix by the original correction coefficients of the corresponding columns to obtain a preliminarily corrected gray value matrix; dividing the gray value of each pixel in the preliminarily corrected gray value matrix by the median value of the row to determine the pixel response non-uniformity coefficient of the initial row in the pixel matrix of the screen to be inspected; obtaining effective flat-field correction coefficients to correct the gray-scale image taken by the linear array camera. The method of the technical scheme of the invention aims at the problems that the current flat field correction method of the linear array camera is difficult to adapt to the difference of the working environment and the precision is not high, and under the actual working condition, the flat field correction of the linear array camera is carried out through the combination of the optics and the algorithm, which has good adaptabilityand high precision.

The invention discloses a cloth surface defect detection device and method based on machine vision. The detection device is assembled by modules, and comprises a preprocessing module, a visual detection module and a rolling module. The method comprises the steps of: using an area-array camera module in the visual detection module to shoot a defect-free cloth image as a standard sample, calculating a flat field correction matrix according to the standard sample, and realizing brightness compensation; calculating a clustering center and other characteristic parameters of the standard sample by adopting a principle of a K-means clustering algorithm; shooting cloth to be detected in real time and performing flat-field correction by the area-array camera module; carrying out edge detection and area cutting according to a brightness value difference between the background and the cloth image; calculating the Euclidean distance from a pixel of a to-be-detected image to a clustering center, and judging whether defects exist or not according to a threshold value; and if so, storing the defect image. The problems that traditional manual visual inspection is low in detection speed, low in precision, high in omission ratio and high in false detection rate are solved, and automatic detection development in the textile field is promoted.

The invention discloses an image grey value based mask optical defect detecting method. The method includes steps: acquiring bright area data and dark area data of an actual image on a camera interface; adopting a camera flat field correction function for camera view field brightness correction of the actual image to guarantee value maintenance of grey values of a bright area and a dark area in aview field, and keeping uniform as far as possible; selecting a dark area on a calibration plate of the actual image, and calibrating a grey value to be V1; selecting a bright area on the calibrationplate of the actual image, and calibrating a grey value to be V2; recording the calibrated grey value V1 of the dark area and the calibrated grey value V2 of the bright area into a Recipe template toserve as subsequent mask detection parameters, and directly applying the subsequent mask detection parameters as grey values of standard image generation bitmap to keep uniformity of the grey values of the actual image and the grey values of a standard image as far as possible; after image registration, subjecting the actual image and the standard image to absolute subtraction operation to furtherjudge whether the actual image has defects or not. By adoption of the method, defect detection accuracy can be improved, and great detection effects are achieved.

The invention provides an automatic calibration method for a visual detection system. The automatic calibration method comprises the steps of obtaining a calibration target image shot by a to-be-calibrated camera; calculating a definition value, a resolution value and distortion deformation according to the calibration target image, and adjusting the lens focal length of the to-be-calibrated camera; obtaining a vertical line image according to the calibration target image, and adjusting the position of the to-be-calibrated camera relative to the calibration target; generating a gray scale curve according to the calibration target image, and adjusting the position of the to-be-calibrated light source relative to the to-be-calibrated camera; obtaining an image gray value according to the calibration target image, and carrying out white balance correction and flat field correction on the to-be-calibrated camera; and calculating the signal-to-noise ratio of the edge region and the signal-to-noise ratio of the central region of the image. According to the invention, automatic, rapid and accurate calibration of different types of detection systems is realized through a standardized process, the consistency of calibration evaluation standards is ensured, and the accuracy and efficiency of visual detection system calibration are improved.

Methods, apparatuses, and systems for imaging biological / chemical samples are provided. A calibrated imaging system can allow a user to obtain an optimal focus setting (position) for any effective distance (e.g. a zoom setting). The optimal focus can be determined from a functional approximation that defines a relationship between effective distance and focus setting. A user can input a size, and an imaging system can determine the appropriate effective distance and focus. An imaging system can also determine a size based on any effective distance. A flat-field correction can also be determined for any effective distance or size.

The invention relates to a method for correcting a flat field of two-dimensional optical detection. A first optical filter is arranged between a CCD (Charge Coupled Device) and at least one reference illuminator. The reference illuminator is moved relative to the CCD, so as to utilize the CCD to capture a plurality of individual images and integrate a flat field message. Accordingly, a first light intensity correcting field profile is calculated, thereby obtaining a first light intensity correcting rate corresponding to each image coordinate in an image coordinate system of CCD. After a deviated projecting detection image of at least one to-be-detected illuminator is captured by the CCD, a corrected light intensity value corresponding to each image coordinate in the deviated projecting detection image is calculated according to the first light intensity correcting rate, so as to obtain a light intensity correcting detection image.

The invention provides a flat field correction parameter acquisition method and device. The method comprises the following steps: acquiring a dark field image of a to-be-corrected image; calculating and storing a dark field row mean vector and a dark field column mean vector; calling the stored dark field row mean vector, and calculating a dark field row mean matrix; calling the stored dark field column mean vector, and calculating a dark field column mean matrix; adding the dark field row mean value matrix and the dark field column mean value matrix to obtain an FPN parameter of each dark field pixel point; obtaining a PRNU parameter of each bright field pixel point in the bright field image of the to-be-corrected image; and outputting the FPN parameter and the PRNU parameter as a flat field correction parameter of each to-be-corrected pixel point in the to-be-corrected image. According to the method, only the row mean vector and the column mean vector of the to-be-corrected image need to be stored, the parameter data size needing to be stored during flat-field correction is reduced, and the flat-field correction parameters with the same data size after flat-field correction parameter calculation is carried out on pixel points in the to-be-corrected image one by one can be obtained.

The invention discloses a high-precision farmland vegetation information extraction method, and relates to the technical field of agricultural remote sensing, and the technical scheme is characterized in that the method comprises the following steps: S1, collecting an original farmland image; S2, performing flat field correction processing on the farmland original image; S3, importing the image data after the flat field correction processing into Pix4Dmapper or ENVI software, and carrying out the image splicing and cutting; S4, labeling the image data, and formulating a neural network data set through a preprocessing mode of data enhancement and image cutting; S5, constructing and training a Unet neural network model; S6, saving the model, inputting a farmland image to be identified into the saved model, and obtaining an extracted farmland vegetation texture and spatial distribution information result. According to the method, the texture and spatial distribution information of the crops can be quickly and accurately obtained from the remote sensing image of the farmland, the problems of complex manual screening features and low recognition precision existing in satellite remote sensing interpretation of the farmland image are solved, and a reference method is provided for remote sensing interpretation of farmland crop information by an unmanned aerial vehicle.

The embodiment of the invention discloses a lens distortion compensation method and device, equipment and a storage medium. The lens distortion compensation method comprises the following steps: acquiring current acquisition parameters of image acquisition equipment, wherein the current acquisition parameters comprise a lens parameter, an aperture parameter and a distance parameter; determining atarget correction coefficient curved surface of the image acquisition equipment according to the current acquisition parameters; and performing brightness compensation on a to-be-compensated image acquired by the image acquisition equipment according to the target correction coefficient curved surface. According to the embodiment of the invention, when the acquisition parameters of the image acquisition equipment are changed; the correction coefficient of the image acquisition equipment under the current acquisition parameter can be obtained without carrying out flat field correction on the image acquisition equipment; the determination speed of the correction coefficient of the image acquisition equipment can be improved, the lens distortion compensation speed of the image acquisition equipment is further improved, and manpower and material resources consumed by lens distortion compensation of image acquisition parameters are reduced.

The invention provides a white balance processing method and device for a camera system. The method comprises the steps of carrying out flat-field correction on all pixels of the camera system to obtain a grayscale correction value of a reference channel and a grayscale correction value of a channel to be calibrated under a white reference object of the camera system; obtaining a white balance gain value of the channel to be calibrated relative to the reference channel according to the ratio of the grayscale correction value of the channel to be calibrated and the grayscale correction value ofthe reference channel; and obtaining a white balance correction value of the channel to be calibrated according to the product of the grayscale correction value and the white balance gain value of the channel to be calibrated. The embodiment of the invention carries out white balance processing on the basis of the flat-field correction, simplifies the processing steps of a white balance algorithmand improves the accuracy of the white balance.

An embodiment of the invention relates to a target extraction and flat-field correction method for imaging system with large difference in gain. The target extraction and flat-field correction method is designed for that the imaging system of larger difference cannot recognize current situation of an observed object in an original observed image. The method comprises the steps of establishing a certain uniform face light source system and shooting a light source image; acquiring images that the multi-frame observed target is in different place; utilizing the certain uniform face light source to deduct uneven background of each frame observed image and extracting feature information of the observed object; rectifying the image sequencing in different places of a detector based on obtained features of the observed object; utilizing a fundamental principle that an intensity ratio of the observed object in different places of the detector is equal to a gain ration in different places to iterate the flat field; utilizing the flat field image of iteration to carry out the flat field correction to the observed target image so as to complete calibration of accurate luminosity of the observed object.