Example methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to implement global tone mapping of images based on luminance and chrominance are disclosed. Examples disclosed herein determine a chromatic gain to apply to input chrominance components corresponding to an input color of a pixel of the input image, the chromatic gain based on an input luminance component corresponding to the input color of the pixel and a luminance gain to be applied to the input luminance component of the pixel to determine an output luminance component of the pixel. Disclosed examples also apply the chromatic gain to the input chrominance components of the pixel to determine output chrominance components of the pixel. Disclosed examples further combine the output luminance component and the output chrominance components to determine an output color of the pixel.

A method for distributing High Dynamic Range (HDR) content to playback devices for displaying images where the HDR content is encoded to an HDR bitstream and the HDR bitstream is subsequently decoded by a playback device. The HDR bitstream contains auxiliary metadata packets that are based upon the processing capability of the playback device.

An electronic device includes a UDC and a UDC controller configured to determine an optimal number of frames required to be captured for a scene to compensate at least one parameter to optimize an output media using the UDC, obtain a multi-frame fusion media by performing at least one multi-frame fusion on the determined optimal number of frames, perform a light source spread correction on the multi-frame fusion media, and optimize the output media based on the light source spread correction on the multi-frame fusion media.

Provided are a video conversion method, an electronic device and a non-transitory computer readable storage medium. The implementation scheme is as follows: a to-be-converted SDR video is acquired; one frame is extracted from the to-be-converted SDR video to serve as a current SDR image, the current SDR image is input into a parameter predictor and a generator, and an adjustment parameter corresponding to the current SDR image is output from the parameter predictor; the adjustment parameter corresponding to the current SDR image is input into the generator, and an HDR image corresponding to the current SDR image is output from the generator; and the operation described above is repeatedly performed until frames are converted into HDR images each of which corresponds to a respective frame of the frames; and a corresponding HDR video is generated based on the HDR images corresponding to the frames.

Devices, methods, and computer-readable media are disclosed describing an adaptive approach for image bracket selection and fusion, e.g., to generate low noise and high dynamic range (HDR) images in a wide variety of capturing conditions. An incoming image stream may be obtained from an image capture device, wherein the incoming image stream comprises a variety of differently-exposed captures, e.g., EV0 images, EV− images, EV+ images, long exposure (or synthetic long exposure) images, EV0/EV− image pairs, etc., which are received according to a particular pattern. When a capture request is received, a set of rules and/or a decision tree may be used to evaluate one or more capture conditions associated with the images from the incoming image stream and determine which two or more images to select for a fusion operation. A noise reduction process may optionally be performed on the selected images before (or after) the registration and fusion operations.

An image processing method and a device configured to implement the same are disclosed. The method comprises: obtaining optical input from a hybrid imaging device, wherein an obtained optical input comprises a first component and a second component that temporally corresponds to the first component; wherein the first component of the obtained optical input corresponds to a first temporal resolution, while the second component of the obtained optical input corresponds to a second temporal resolution higher than that of the first component; performing image restoration operation on a first subset of the first component of the obtained optical input in accordance with data from the second component of the obtained optical input; and performing image fusion operation to generate fused image data from an output of the image restoration operation and a second subset of the first component of the obtained optical input.

A digital graduated filter is implemented in an imaging device by combining multiple images of the subject wherein the combining may include combining different numbers of images for highlights and for shadows of the subject. The imaging device may present a user with a set of pre-defined graduated filter configurations to choose from. A user may also specify the direction of graduation and strength of graduation in a viewfinder. In an alternative implementation, combining may include scaling of pixels being added instead of varying the number of images being combined. In an alternative implementation, the combining of multiple images may include combining a different number of images for highlights of the subject than for shadows of subject.

A method for image capture includes identifying a bright spot in an image. A neural network is used to recover details in bright spot area through a trained de-noising process. Post-processing of the image is conducted to match image parameters of recovered details in the bright spot area to another area of the image.

Disclosed is a display apparatus. The display apparatus obtains first characteristic information, which is provided according to a plurality of sections of content and corresponds to an image characteristic of a section to be displayed among the plurality of seconds, from a signal received in the signal receiver, obtains first image-quality setting information for setting image quality of the section based on the obtained first characteristic information, obtains second characteristic information corresponding to an image characteristic of a frame included in the section from the frame, obtains second image-quality setting information for setting image quality of the frame based on the obtained first image-quality setting information and the obtained second characteristic information, and controls the display to display an image of the frame, the image quality of the frame being set based on the obtained second image-quality setting information.

The various embodiments of the present disclosure are directed towards methods for tone mapping High-Dynamic-Range (HDR) image data, as well as controlling the brightness of the image encoded by HDR the image data and/or the tone-mapped image data. HDR image is captured. A tone mapping function for the HDR image data is generated. To generate the tone mapping function, control points are dynamically determined based on an analysis of the HDR image data. The tone mapping function is fit to the control points. The tone mapping function is a non-linear function, and is described by a curve in a plane. The shape of the curve is constrained by a line generated from a portion of the control points. The tone mapping function is applied to the HDR image data. A color-compression is applied to the tone mapped image data to generate Standard Dynamic Range or Low Dynamic Range image data.