A method for measuring distorted illumination patterns and correcting image artifacts in structured illumination microscopy. The method includes the steps of generating an illumination pattern by interfering multiple beams, modulating a scanning speed or an intensity of a scanning laser, or projecting a mask onto an object; taking multiple exposures of the object with the illumination pattern shifting in phase; and applying Fourier transform to the multiple exposures to produce multiple raw images. Thereafter, the multiple raw images are used to form and then solve a linear equation set to obtain multiple portions of a Fourier space image of the object. A circular 2-D low pass filter and a Fourier Transform are then applied to the portions. A pattern distortion phase map is calculated and then corrected by making a coefficient matrix of the linear equation set varying in phase, which is solved in the spatial domain.

A first frame of time of flight (TOF) data including projection off data and infrared data is obtained, and after determining that a data block satisfying that a number of data points with values greater than a first threshold is greater than a second threshold is present in the infrared data, TOF data for generating a first frame of a TOF image is obtained based on a difference between the infrared data and the projection off data. Because the data block satisfying the number of data points with values greater than the first threshold is greater than the second threshold is an overexposed data block, and the projection off data is TOF data acquired by a TOF camera with a TOF light source being off, the difference between the infrared data and the projection off data can correct the overexposure, improving quality of the first frame of the TOF image.

Techniques for facilitating non-uniformity correction calibrations are provided. In one example, an infrared imaging system includes an infrared imager and a logic device. The infrared imager is configured to capture a first set of infrared images of a reference object using a first integration time. The infrared imager is further configured to capture a second set of infrared images of the reference object using a second integration time different from the first integration time. The logic device is configured to determine a dark current correction map based on the second set of infrared images. The logic device is further configured to generate a non-uniformity correction map based on the dark current correction map. Related devices and methods are also provided.

Disclosed are an image synthesis method and a related apparatus, the method includes: determining a target area on a preview image by means of eyeball tracking technology; on the basis of brightness parameters of the target area, determining multiple exposure parameter sets; setting a camera module with the multiple exposure parameter sets to acquire multiple reference images, each reference image corresponding to a different exposure parameter set; and synthesizing the multiple reference images to obtain a target image.

A method and device for testing product quality are disclosed. The method for testing product quality comprises: acquiring an image of a product to be tested; testing the image by using a pre-trained neural network model to obtain a testing result output by the neural network model; when the testing result indicates that the product to be tested is a defective product, performing a secondary judgment on the testing result according to position information of defective feature pixels in the image in the testing result, and determining whether the product to be tested is qualified according to a secondary judgment result. The method has high test accuracy, ensures the quality of product and facilitates reducing the labor cost of test.

Embodiments of the present invention are a high dynamic range (HDR) synthesis method and apparatus, an image processing chip and an aerial camera. The method includes: acquiring a plurality of to-be-synthesized images having different exposure time; calculating a mean brightness of the to-be-synthesized images; determining an image brightness type of the to-be-synthesized images according to the mean brightness; calculating a brightness difference between adjacent pixel points in one to-be-synthesized image; calculating an inter-frame difference of different to-be-synthesized images at a same pixel point position according to the brightness difference; determining a motion state of the to-be-synthesized images at the pixel point position according to the inter-frame difference; and weighting and synthesizing the to-be-synthesized images into a corresponding HDR image according to the image brightness type and the motion state.

An electronic device is provided. The electronic device includes a memory, an image sensor including light receiving elements each including at least two sub light receiving elements, and an image signal processor. The image signal processor is configured to obtain images corresponding to light from outside by using the image sensor, the images including at least a raw image, a first sub image, and a second sub image, the first sub image being an image corresponding to light detected by at least one first sub light, the second sub image being an image corresponding to light detected by at least one second sub light, identify a luminance ratio between the first sub image and the second sub image, identify a defect in the raw image, based on the luminance ratio, and perform a function corresponding to a type of the defect.

Method for detecting a defect in a zone of interest of an optical lens, the method including: an image reception step, during which a plurality of images is received, each image includes a view of the zone of interest in front of a plurality of specific patterns, each specific pattern including a bright area and a dark area, and at least one image received is saturated in light intensity; a sampling step, during which each image of the plurality of images are sampled based on a common sampling pattern; a recombination step, during which a recombined image of the zone of interest is determined based on the common sampling pattern; and a defect detection step, during which a defect is detected in the zone of interest of the optical lens based on an analysis of the recombined image.

A noise removing circuit includes an image combiner suitable for generating a high dynamic range (HDR) image by combining images having different exposure times; a detailed image generator suitable for generating a detailed image from the HDR image; an image strength evaluator suitable for evaluating strength of the detailed image; and a noise coring component suitable for performing a noise coring operation for removing noise from a region of the detailed image in which a signal to noise ratio (SNR) has decreased using a low threshold and a saturation threshold when the strength of the detailed image is less than a reference value.

Method for detecting containers which have fallen over and/or are damaged in a container mass flow, wherein the containers in the container mass flow are transported vertically on a transporter, wherein the container mass flow is captured as an image data stream using at least one camera, and wherein the image data stream is evaluated by an image processing unit, wherein the image data stream is evaluated by the image processing unit using a deep neural network in order to detect and locate the containers which have fallen over and/or are damaged.