A method for generating a relighted image includes: obtaining a to-be-processed image and a guidance image corresponding to the to-be-processed image; obtaining a first intermediate image consistent with an illumination condition in the guidance image by performing relighting rendering on the to-be-processed image in a time domain based on the guidance image; obtaining a second intermediate image consistent with the illumination condition in the guidance image by performing relighting rendering on the to-be-processed image in a frequency domain based on the guidance image; and obtaining a target relighted image corresponding to the to-be-processed image based on the first intermediate image and the second intermediate image.

Methods, systems, and media for modifying user interface colors are provided. In some embodiments, the method comprises: receiving a video and color palette information, wherein each color of the color palette information indicates a color of an element of a user interface in which the video is to be presented; identifying a first color for the element, wherein the first color corresponds to a first portion of the video; causing the first portion of the video to be presented, wherein the element of the user interface having the first color is presented; identifying a second color for the element, wherein the second color corresponds to a second portion of the video; and modifying an appearance of the element by changing the color of the element from the first color to the second color while presenting the second portion of the video.

Systems, apparatuses and methods may a performance-enhanced computing system comprising a sensor for measuring luminance values corresponding to light focused onto the sensor at a plurality of pixel locations, a memory including a set of instructions, and a processor. The processor executes a set of instructions causing the system to generate a multi-segment tone mapping curve, generate a set of tone mapping values corresponding to the multi-segment tone mapping curve for equally spaced input values between zero and one for storage into a look up table, and process the luminance values using the look up table to apply the tone mapping curve to the luminance values of the pixels.

Disclosed are devices, systems and methods for processing an image. In one aspect a method includes receiving an image from a sensor array including an x-y array of pixels, each pixel in the x-y array of pixels having a value selected from one of three primary colors, based on a corresponding x-y value in a mask pattern. The method may further include generating a preprocessed image by performing preprocessing on the image. The method may further include performing perception on the preprocessed image to determine one or more outlines of physical objects.

An image stitching method includes: receiving a first image and a second image; determining that both the first image and the second image include a target object; obtaining a first brightness value and a second brightness value, the first brightness value being a brightness value of the target object in the first image, and the second brightness value being a brightness value of the target object in the second image; adjusting a brightness value of the first image and a brightness value of the second image according to the first brightness value and the second brightness value, so as to obtain a first image to be stitched and a second image to be stitched; and stitching the first image to be stitched and the second image to be stitched to obtain a first stitched image.

An image enhancement system and method based on a generative adversarial network (GAN) model. The image enhancement system includes an acquiring unit, a training unit and an enhancement unit. The acquiring unit is configured to acquire a first image of a driving environment captured by a camera of a first vehicle and a second image of the driving environment captured by a camera of a second vehicle. The training unit is configured to train a GAN by using the first training image to obtain an image enhancement model. The enhancement unit is configured to enhance the second image by inputting the second image into the image enhancement model.

A minimum luminance value of a display luminance information is larger than a minimum luminance value of a print luminance information. And in a conversion, a luminance value of a dark region of input image data is converted to a luminance value of a dark region of output image data such that a contrast of a dark region that includes the minimum luminance value of the print luminance information becomes closer to a contrast of a dark region that includes the minimum luminance value of the display luminance information.

Described are methods and devices for applying a color gamut mapping process on a first image to generate a second image, where the content of the first and second images is similar but the respective color spaces of the first and second images are different. The color gamut mapping process may be controlled using a color gamut mapping mode obtained from a bitstream where the color gamut mapping mode belongs to a set comprising at least two preset modes and an explicit parameters mode. If the obtained color gamut mapping mode is the explicit parameters mode and the color gamut mapping process is not enabled for the explicit parameters mode, the color gamut mapping process may be controlled by a substitute color gamut mapping mode determined from additional data.

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.

The present invention provides image processing apparatus, an image processing system and an image processing method, whereby the accuracy of evaluation can be improved. Image processing apparatus for correcting a captured image includes an image acquisition unit that acquires block pixels, an image conversion unit that converts the lightness/darkness, density, luminance and color space of the image based on the RGB values contained in the block pixels, and an output unit that outputs the converted image, and the image conversion unit further includes a binarization processing unit that binarizes the image, calculates the area ration of lightness and darkness in the image, and specifies the light and dark fields, a density conversion unit that performs conversion into wavelengths corresponding to the RGB values, a luminance conversion unit that performs conversion into luminance of the maximum wavelength that is visible to human eye, and a color-space conversion unit that performs conversion into HSV values representing a color space of color tones.