A method includes obtaining multiple image frames of a scene using at least one sensor of an electronic device. The multiple image frames include a first image frame and a second image frame having a longer exposure than the first image frame. The method also includes generating a label map that identifies pixels in the multiple image frames that are to be used in an image. The method further includes generating the image of the scene using the pixels extracted from the image frames based on the label map. The label map may include multiple labels, and each label may be associated with at least one corresponding pixel and may include a discrete value that identifies one of the multiple image frames from which the at least one corresponding pixel is extracted.

Systems and methods for tone mapping of high dynamic range (HDR) images for high-quality deep learning based processing are disclosed. In one embodiment, a graphics processor includes a media pipeline to generate media requests for processing images and an execution unit to receive media requests from the media pipeline. The execution unit is configured to compute an auto-exposure scale for an image to effectively tone map the image, to scale the image with the computed auto-exposure scale, and to apply a tone mapping operator including a log function to the image and scaling the log function to generate a tone mapped image.

Systems and methods for dynamically computing display properties of an overlay on a base image are disclosed. The method receives base image data and its properties, and overlay data and its position on the base image. The method identifies a set of pixels of the base image situated under at least a portion of the overlay. For each pixel in the set of pixels, the method computes a value of a display property of the pixel. The method then computes a reference display property value of the base image based on the computed display property values of pixels and computes a display property value of the overlay using the computed reference display property value of the base image. The method then assigns a display property of the overlay based on the computed display property value of the overlay.

The present disclosure relates to an artificial intelligence (AI) system utilizing a machine learning algorithm, including deep learning and the like, and application thereof. In particular, an electronic device of the present disclosure comprises: a memory including at least one command; and a processor connected to the memory so as to control the electronic device, wherein, by executing the at least one command, the processor acquires an image, acquires a noise correction map for correction of noise of the image on the basis of configuration information of a camera having captured the image or brightness information of the image, and eliminates the noise of the image through the noise correction map. In particular, at least a part of an image processing method may use an artificial intelligence model having been acquired through learning according to at least one of a machine learning algorithm, a neural network algorithm, and a deep learning algorithm.

Systems and methods for generating a visually enhanced image of a digital document are disclosed. In one example, a method includes receiving, by a computing device, a selection of an original document to be viewed by a user; obtaining, by the computing device, visual annotations for the original document from a remote computing device, wherein the visual annotations indicate one or more visual effects parameters associated with one or more pages of the original document; determining, by the computing device, visual effects to be applied to one or more pages of the original document based on the visual annotations; and applying the visual effects to render, by the computing device, a visually enhanced version of the original document for viewing by the user.

Disclosed are a content providing apparatus, a method of controlling the same, and a recording medium thereof, the content providing apparatus including: a transmitter configured to transmit data to a display apparatus; and a processor configured to control the transmitter to transmit content data and additional data, relating to image attributes of the content data and having a fixed value corresponding to at least one section, among a plurality of sections of the content data, to the display apparatus based on a command received from a user to playback image content at a predetermined speed. Thus, it is possible to solve a problem of flickering or an error in brightness of a screen at a variable-speed playback of dynamic HDR content.

A radiation image acquisition system includes a radiation source that outputs radiation toward an object, a scintillator that has an input surface to which the radiation output from the radiation source and transmitted through the object is input, converts the radiation input to the input surface into scintillation light, and is opaque to the scintillation light, an image capturing means that includes a lens portion focused on the input surface and configured to image the scintillation light output from the input surface and an image capturing unit configured to capture an image of the scintillation light imaged by the lens portion and outputs radiation image data of the object A, and an image generating unit that generates a radiation image of the object based on the radiation image data output from the image capturing means.

An apparatus includes a resolving unit configured to resolve input image data into image data for each frequency band, an acquisition unit configured to acquire skewness corresponding to the resolved image data resolved by the resolving unit, wherein the skewness is acquired from a histogram corresponding to each of the resolved image data, and an adjustment unit configured to determine image data to be processed, out of the resolved image data based on the acquired skewness acquired and perform gain adjustment on the determined image data.

A facial image-processing method includes: transforming a facial image with 2D Fourier transformation (FT) in a template to obtain 2D FT data of color channels of the facial image and a 2D FT data of the template, with computing first light intensities of color channels and a second light intensity of the template with the 2D FT data; computing an intensity mean value and an intensity maximum in each of the color channels; processing the first light intensities and the second light intensity with singular value decomposition (SVD) to obtain intensity spectrum SVD matrixes and a template SVD matrix; computing a compensation weight coefficient for each color channel with the intensity mean value, the intensity maximum and SV maximums of the intensity spectrum SVD matrixes and the template SVD matrix; and compensating the facial image with the compensation weight coefficients to obtain a compensated facial image.

A setting apparatus comprises a setting unit that sets a virtual light parameter for applying an effect of irradiating virtual light on a plurality of subjects included in an image; and a classification unit that classifies the plurality of subjects into a plurality of groups based on a state of shadow. The setting unit sets the virtual light parameter for each group classified by the classification unit.