State information indicating states of a plurality of imaging apparatuses 100-x used for generating a virtual viewpoint image is acquired. At least one image type is determined from a plurality of image types indicating display formats of displaying the states of the plurality of imaging apparatuses 100-x based on the state information. Based on the determined image type, the states of the plurality of imaging apparatuses 100-x are displayed.

An image signal processor and an image sensor including the same are disclosed. An image sensor includes a pixel array configured to convert received optical signals into electrical signals, a readout circuit configured to convert the electrical signals into image data and output the image data, and an image signal processor configured to perform deep learning-based image processing on the image data based on training data selected from among first training data and second training data based on a noise level of the image data.

A calibration operation support device is applied to a system including an industrial camera and a display device displaying a predetermined image that is an image of a predetermined area being captured by the industrial camera, and includes a processing device configured to perform a calibration of the industrial camera based on captured images that are obtained by capturing a calibration pattern by the industrial camera. The processing device is further configured to instruct the display device to display positions of the calibration patterns in the captured images acquired as images to be used for the calibration in a manner superimposed on the predetermined image.

A method operable by circuitry including an image processor, an image sensor, and another clock-dependent device, including measuring a flicker using the image sensor, adjusting a clock rate of the circuitry according to the measured flicker, and operating the clock-dependent device using the adjusted clock rate.

A method for calibrating image distortion, apparatus, electronic device, and computer readable storage medium are disclosed. The method for calibrating image distortion includes: obtaining an original image captured by a camera; calculating a deformation degree of foreground objects when the original image includes the foreground objects; and performing a distortion calibration and a spherical projection on the original image to obtain a target image when the deformation degree of the foreground objects is greater than a predetermined threshold. The method for calibrating image distortion provided by the disclosure can realize fast distortion calibration of ultra-wide-angle image with low computational complexity and obtain better calibration effect.

A test device which is convenient for fast testing of cameras being mass-produced and providing a test environment without contamination by reflected light, comprises a housing, a mounting member, a test card, and a light source assembly. The housing is a testing cavity and, at opposite ends, defines a testing hole and a light through hole lined up on center axis of the housing. A distance between an inner wall of the housing and the central axis gradually increases from the testing hole to the light through hole. The test card is arranged in the testing cavity. The light source assembly is connected to the mounting member and covers the light through hole. Sides of the housing illuminated by the light source assembly absorb all light emitted by the light source assembly.

Disclosed herein is a system and method directed to object tracking and metric generation using a plurality of cameras. The system includes the plurality of cameras disposed around a playing surface in a mirrored configuration, where the plurality of cameras are time-synchronized. The system further includes logic that, when executed by a processor, causes performance of operations including: obtaining a sequence of images from the plurality of cameras, continuously detecting an object in image pairs at successive points in time, wherein each image pair corresponds to a single point in time, continuously determining a location of the object within the playing space through triangulation of the object within each image pair, detecting a player and the object within each image of a subset of image pairs of the sequence of images, identifying a sequence of interactions between the object and the player, and storing the sequence of interactions.

The present invention relates to a wide-angle image providing method including: an image taking step of generating a first region image obtained by taking an image of a first region and generating a second region image obtained by taking an image of a second region adjacent to the first region by a second camera module; a distortion calibration step of correcting distortion of each of the first and second region images by a distortion calibration unit; a phase difference calibration step of correcting a phase difference of each of the first and second region images; an overlap calibration step of correcting the first and second region images while overlapping the first and second region images to be adjacent to each other by an overlap calibration unit; and a color calibration step of correcting colors of the first and second region images which have been overlapped and calibrated.

The present application discloses an image processing method, apparatus, device and storage media. A specific implementation solution is: obtaining an original image and a noise-added image, where the noise-added image is an image of the original image after a noise is added, and a number of pixels with a noise in the original image is less than a preset number; encoding and decoding the original image and the noise-added image respectively, to obtain a first decoded image corresponding to the original image and a second decoded image corresponding to the noise-added image; obtaining a first PSNR between the first decoded image and the original image according to the original image and the first decoded image; obtaining a second PSNR between the second decoded image and the noise-added image according to the noise-added image and the second decoded image; and outputting the first PSNR and the second PSNR.

Systems and methods for calibrating non-spatial measurements of a device under test (DUT) for misalignment between the DUT and a non-spatial measurement device are disclosed herein. A system for generating a misalignment calibration database can include, for example, a non-spatial measurement device and a high-precision translation stage. The system can generate a misalignment calibration database by taking measurements of a DUT at multiple misalignment locations. A system for measuring a DUT can include, for example, a spatial measurement device, a non-spatial measurement device, a translation stage, and/or a carrier tray. The system can capture measurements of the DUT at a first position and calibrate the measurements for misalignment using calibration data corresponding to the first position. For example, the system can retrieve calibration data from a calibration misalignment system that was taken at the same and/or different locations proximate the position of the DUT.