A method for enhancing an image and an image enhancement device are described. The method for enhancing an image including: capturing an initial image including a plurality of pixels, and performing a pixel-by-pixel dehazing operation for each of the plurality of pixels. The performing including: generating, for each of the plurality of pixels, a value for a blended gray image based on color channels of the pixel, generating, for each of the plurality of pixels, a value for a transmission map based on the blended gray image, and generating, for each of the plurality of pixels, output color channels for a processed image based on the value for the transmission map, the processed image being an enhancement of the initial image.

An information processing apparatus acquires imaging parameters of a first imaging apparatus and a second imaging apparatus, and based on the imaging parameters, determines a number of first images to be captured by the first imaging apparatus and a number of second images to be captured by the second imaging apparatus. Further, the information processing apparatus acquires first color information included in the first images and second color information included in the second images, and based on the first color information and the second color information, generates color correction information for correcting a difference in color between the first and second images.

A system, method, and computer program product are provided for exchanging images. In use, one or more images are received at a server. Additionally, the one or more images are analyzed. Further, image processing code is outputted referencing the one or more images, based on the analysis of the one or more images. Additional systems, methods, and computer program products are also presented.

The present invention provides a display screen with an integrated video camera optimized to capture the display screen’s information and a light source that injects colored light into the edge of the display screen. Additionally, the system comprises a color blending instrument to blend the primary colors of red, green, blue, and a combination thereof to create an unlimited variety of color combinations that are injected into the display screen.

An image processing apparatus and a method are provided. The apparatus comprises a plurality of processing modules configured to operate in series to refine a raw image captured by a camera, the modules comprising a first module and a second module, each of which independently implements a respective trained artificial intelligence model, wherein: the first module implements an image transformation operation that performs an operation from the set comprising: (i) an essentially pixel-level operation that increases sharpness of an image input to the module, (ii) an essentially pixel-level operation that decreases sharpness of an image input to the module, (iii) an essentially pixel-block-level operation on an image input to the module; and the second module as a whole implements a different operation from the said set.

Techniques are described for efficient staggered high-dynamic-range (HDR) output of an image captured using a high-pixel-count image sensor based on pixel binning followed by luminance-guided upsampling. For example, an image sensor array is configured according to a red-green-blue-luminance (RGBL) CFA pattern, such that at least 50-percent of the imaging pixels of the array are luminance (L) pixels. In each image capture time window, multiple (e.g., three) luminance-enhanced (LE) component images are generated. Each LE component image is generated by exposing the image sensor to incident illumination for a respective amount of time, using pixel binning during readout to generate appreciably downsampled color and luminance capture frames, generating an upsampled luminance guide frame from the luminance capture frame, and using the upsampled luminance guide frame to guide upsampling (e.g., and remosaicking) of the color capture frame. The resulting LE components images can be digitally combined to generate an HDR output image.

Methods, systems, devices, and tangible non-transitory computer readable media for haze reduction are provided. The disclosed technology can include generating feature vectors based on an input image including points. The feature vectors can correspond to feature windows associated with features of different portions of the points. Based on the feature vectors and a machine-learned model, a haze thickness map can be generated. The haze thickness map can be associated with an estimate of haze thickness at each of the points. Further, the machine-learned model can estimate haze thickness associated with the features. A refined haze thickness map can be generated based on the haze thickness map and a guided filter. A dehazed image can be generated based on application of the refined haze thickness map to the input image. Furthermore, a color corrected dehazed image can be generated based on performance of color correction operations on the dehazed image.

A method for suppressing chromatic aberration, especially blue or red fringing, in a digital image with multiple color channels is disclosed. The method comprises negatively correcting a first color channel by subtracting an overshoot component of the first color channel. The subtraction is subject to a lower threshold, which is dependent on a local value of at least one further color channel.

An image processing apparatus includes a first filter unit and a first composition unit. The first filter unit generates a plurality of results of filter processing for brightness by individually applying each of a plurality of filters for brightness with different frequency bands to a first brightness component image indicating a distribution of brightness components in a first image. The plurality of filters for brightness are spatial filters based on a visual characteristic of a human related to contrast detection. The first composition unit generates brightness contrast influence information indicating a distribution of degrees of influence of brightness contrast in the first image by compositing together the plurality of results of filter processing for brightness.

Ways to generate, store, and distribute optimized content are described. Content modification operations including color correction are stored as metadata that is embedded in each content item. The metadata is extracted in order to eliminate or update the modification operations. Modification operations are updated based at least partly on profiles associated with one or more content provision elements. The profiles include device profiles and codec profiles. Each profile may be specific to a particular element or be a generic profile associated with multiple elements. The profiles are generated based on evaluation of the devices and codes and are stored as entries in a look up table. When content is provided, the profiles are used to optimize the content for display.