An image detection obtains original image. The original image is corrected to obtain a corrected image. Median filtering is performed on the corrected image to obtain a filtered image. A contrast of the filtered image is adjusted to obtain an adjusted image. Bilateral filtering is performed on the adjusted image to obtain an enhanced image. Defects in the enhanced image is detected. The method can detect defects in images accurately and efficiently.

Systems, devices, and methods for determining color ambiguity of images or videos. A system includes a color ambiguity score generator, which analyzes an image and determines a color ambiguity score that quantitively indicates a level of color ambiguity that the image is estimated to cause when viewed by a user having color vision deficiency. A local color ambiguity score is generated to quantitively indicate a level of local color ambiguity between (i) an in-image object and (ii) an in-image foreground of that in-image object. A global color ambiguity score is generated to quantitively indicate a level of global color ambiguity between (I) a first in-image object within the image and (II) a second in-image object within that image. The color ambiguity score generator generates the color ambiguity score by utilizing a formula that uses both (A) the local color ambiguity score and (B) the global color ambiguity score.

There is provided a system (100) comprising a light source (110), an imaging unit (120) configured to capture a plurality of images of an subject, wherein each of the plurality of images is captured at an exposure time shorter than the wave period of the pulsed illumination, wherein the pulse frequency of the illumination is not a multiple integral of the frame rate at which the images are captured, and wherein a total time during which the plurality of images is captured is at least half of the wave period of the pulsed illumination, and a control unit (130) configured to: obtain a predetermined number n of candidate images, generate a sorted list of pixels by sorting respective pixels, apply a set of weights to the respective sorted list of pixels, and generate an estimated ambient light corrected image based on the plurality of weighted and sorted lists of pixels.

In some implementations, a method includes: determining a complexity value for first image data associated with of a physical environment that corresponds to a first time period; determining an estimated composite setup time based on the complexity value for the first image data and virtual content for compositing with the first image data; in accordance with a determination that the estimated composite setup time exceeds the threshold time: forgoing rendering the virtual content from the perspective that corresponds to the camera pose of the device relative to the physical environment during the first time period; and compositing a previous render of the virtual content for a previous time period with the first image data to generate the graphical environment for the first time period.

According to certain embodiments, an electronic device comprises a display; a camera disposed under the display; and a processor configured to, obtain a first image using the camera in a first state in which a first portion of the display corresponding to a position where the camera is disposed is in a first mode, obtain a second image, using the camera in a second state in which the first portion of the display is in a second mode, calculate correction values, based on first data for a first area of the first image and second data for a second area of the second image, wherein the second area of the second image corresponds to the first area of the first image, and correct at least one image among a plurality of images, using the correction values, wherein one of obtaining the first image and obtaining the second image is responsive to the other of obtaining the first image and the second image.

A method of preprocessing incoming video data of at least one region of interest from a camera collecting video data having a first field of view is disclosed herein that includes receiving the incoming video data from the camera; preprocessing the incoming video data, by a computer processor, according to preprocessing parameters defined within a runtime configuration file, with the preprocessing including formatting the incoming video data to create first video data of a first region of interest with a second field of view that is less than the first field of view; and publishing the first video data of the first region of interest to an endpoint to allow access by a first subscriber.

One embodiment of an apparatus includes a reference position receiving unit configured to receive intermediate or end panorama reference position information input by a user, and a control unit configured to control an imaging device to begin generating a plurality of images to be used to generate a panoramic image based on the intermediate or end panorama reference position information input by the user after the reference position receiving unit receives the intermediate or end panorama reference position information.

According to some embodiments, a camera captures a plurality of images of substantially the same scene at different exposure levels for each video frame to be captured. These images are then deghosted, merged or fused, and processed using a spatially, and optionally also temporally, varying tonemapping operator, and the resulting image after some further finishing is written into a video stream. In some embodiments, this processing is performed in real time on a graphics processing unit present in the device containing the camera. Other applications are shown and discussed.

A method of controlling parameters for image sensors includes; receiving a first image and a second image, calculating first feature values related to the first image and second feature values related to the second image; generating comparison results by comparing the first feature values of fixed regions and first variable regions of the first image with the second feature values of fixed regions and first variable regions of the second image, and controlling at least one parameter on the basis of the comparison results.

The present disclosure provides a method and apparatus for converting an image format, an electronic device, a computer readable storage medium and a computer program product, relates to the field of artificial intelligence technology such as computer vision and deep learning, and can be applied to intelligent sensing ultra-definition scenarios. A specific implementation of the method includes: acquiring a to-be-converted standard dynamic range image; performing a convolution operation on the standard dynamic range image to obtain a local feature; performing a global average pooling operation on the standard dynamic range image to obtain a global feature; and converting the standard dynamic range image into a high dynamic range image according to the local feature and the global feature.