The present invention discloses a multimedia device for processing a video signal and control method thereof. According to an embodiment of the present invention, the multimedia device includes a controller configured to perform tone mapping, a dynamic contrast function, and a local contrast function. The controller performs the tone mapping not only on an HDR video signal but also on an SDR video signal. When performing the tone mapping on the SDR video signal, the controller amplifies only an intermediate-gradient region without adjusting low-gradient and high-gradient regions. When performing the dynamic contrast function, the controller only an intermediate-gradient region of the video signal without adjusting low-gradient and high-gradient regions. When performing the local contrast function, the controller divides the video signal into blocks, calculates an APL value of each block, and then applies a linear curve based on the APL value.

On-demand, post-production de-mura of a television is described herein. An example system includes a television that comprises a screen and a local de-mura application. The system also includes a mobile device that comprises a mobile de-mura module. In operation, the mobile de-mura module identifies and quantifies mura in the screen of the television for a given IRE index. These operations are repeatedly performed in a measurement loop that iterates over a range of IRE indexes. Raw uniformity data is generated from such iterations. The local de-mura application uses the uniformity data to de-mura the screen and improve gray uniformity performance of the television. Further, the mobile de-mura module and the local de-mura application are configured to fine tune and further de-mura the screen by iterating a verification loop over a range of IRE indexes, wherein operation of the verification loop is substantially similar to operation of the measurement loop.

To improve the display quality of a display device. To provide a method of correcting image data input to the display device. To provide a novel image correction method or an image correction system. Machine learning for a neural network correcting image data input to the display device is performed by the following method: second image data based on an image that is displayed on the display device by input of first image data to the display device is obtained; third image data is generated by obtaining a difference between the first image data and the second image data; fourth image data is generated by adding the first image data and the third image data; and a weight coefficient is updated so that output data obtained by input of the first image data to the neural network is close to the fourth image data.

A method of visualization, characterization, and detection of objects within an image by applying a local micro-contrast convergence algorithm to a first image to produce a second image that is different from the first image, wherein all like objects converge into similar patterns or colors in the second image.

Methods and systems to improve a visual perception of dark scenes in video. An example device includes one or more processors to receive a frame of video segmented into a plurality of sub-regions. A local luminance histogram is generated for each sub-region. A global luminance histogram is generated for the entire frame of video and a global tone mapping curve is generated based on the global luminance histogram. A tone mapping LUT is generated for each sub-region based on the global tone mapping curve and the corresponding local luminance histogram for the sub-region. The frame of video is then modified using the tone mapping LUTs generated for each sub-region and sent to an output device.

Provided are an image processing apparatus and method, which use a maximum display luminance value of a mastering display and a maximum display luminance value of a target display according to luminance characteristics of a current scene of an encoded image.

A method for processing data in a graphics processing unit including receiving an indication that all threads of a warp in a graphics processing unit (GPU) are to execute a same branch in a first set of instructions, storing one or more predicate bits in a memory as a single set of predicate bits, wherein the single set of predicate bits applies to all of the threads in the warp, and executing a portion of the first set of instructions in accordance with the single set of predicate bits. Executing the first set of instructions may include executing the first set of instruction in accordance with the single set of predicate bits using a single instruction, multiple data (SIMD) processing core and/or executing the first set of instruction in accordance with the single set of predicate bits using a scalar processing unit.

An eye tracking apparatus and a light source control method thereof are provided. The eye tracking apparatus includes a plurality of light sources, an image capturer and a controller. The light sources project a plurality of light beams to a target zone. The image capturer captures a display image on the target zone. The controller turn-off light beams corresponding to a part of light sources according to a contrast ratio of the display image.

A method and apparatus can determine lens shading correction for a multiple camera device with various fields of view. According to a possible embodiment, a flat-field image can be captured using a first camera having a first lens for a multiple camera device. A first lens shading correction ratio can be ascertained for the first camera. A second lens shading correction ratio can be determined for a second camera having a second lens for the multiple camera device. The second camera can have a different field of view from the first camera. The second lens shading correction ratio can be based on the first lens shading correction ratio and can be based on the flat-field image acquired by the first camera.

An image processing device includes an invisible image filter separator that separates an invisible detail component, a visible image filter separator that separates a visible base component and a visible detail component, a base luminance color separator that separates a visible luminance base component and a visible color base component, a detail luminance color separator that separates a visible luminance detail component, a detail synthesizer that generates a synthetic luminance detail component, a synthetic luminance component generator that generates a synthetic luminance component, and a luminance color synthesizer that generates a synthetic image.