Methods and systems are disclosed for quantizing images using machine-learning. A plurality of input images are received from a sensor (e.g., a camera), wherein each input image includes a plurality of pixels. Utilizing an image-to-image machine-learning model, each pixel is assigned a new pixel color. Utilizing a mixer machine-learning model, each new pixel color is converted to one of a fixed number of colors to produce a plurality of quantized images, with each quantized image corresponding to one of the input images. A loss function is determined based on an alignment of each input image with its corresponding quantized image via a pre-trained reference machine-learning model. One or more parameters of the image-to-image machine-learning model and the mixer model are updated based on the loss function. The process repeats, with each iteration updating the parameters of the image-to-image machine-learning model and the mixer model, until convergence, resulting in trained models.

Techniques to improve detection and security of images, including formation and detection of matrix-based images. A histogram may be used to determine a most prevalent plurality of colors associated with an environment. A related plurality of colors may be determined based on the most prevalent plurality of colors. A matrix barcode may be generated based on the related plurality of colors.

The disclosure describes a high dynamic range video coding pipeline that may reduce color artifacts and improve compression efficiency. The disclosed pipeline separates the luminance component from the chrominance components of an input signal (e.g., an RGB source video) and applies a scaling of the chrominance components before encoding, thereby reducing perceivable color artifacts while maintaining luminance quality.

Provided are a texture compressing method and a texture compressing apparatus, which compress some color information of a texture block, which is unable to realize all colors included in the texture block by a determined compression bit number, to be stored in a compression data bit of a texture block, which is able to realize all colors included in the texture block by a bit number lower than the determined compression bit number, based on a color distribution of each texture block, and a texture decompressing method and a texture decompressing apparatus corresponding to the texture compressing method and the texture compressing apparatus.

A method of generating a set of halftone parameters. The method comprises assigning a first set of halftone parameters to a first location in a color space, the first location in the color space corresponding to a first color, and assigning a second set of halftone parameters to a second location in the color space, the second location in the color space corresponding to a second color. An interpolating between the first set of halftone parameters and the second set of halftone parameters is performed, based on the first location and the second location, to determine a third set of halftone parameters corresponding to a third location in the color space. The result of the interpolation is output data associating the third set of halftone parameters with a third color corresponding to the third location in the color space. The first set of halftone parameters may represent a relative area coverage of a first colorant combination and the second set of halftone parameters may represent a relative area coverage of a second colorant combination.

The present disclosure includes systems and methods for color transfer. The method includes receiving a target image, and determining dominant source colors. The method further includes transforming the target image into a color model including a target luminance component and a target color information component. Additionally, the method includes segmenting the target image into a plurality of target segments based on the target color information component or the target luminance component and extracting dominant target colors from the target image by extracting information for at least one of the dominant target colors from each target segment of the plurality of target segments. Further, the method includes generating a color mapping relationship between the dominant target colors and the dominant source colors, and creating a recolored target image using the color mapping relationship.

An electronic endoscope processor has a configuration including: a converting means for converting pieces of pixel data that are made up of n (n3) types of color components and constitute a color image in a body cavity into pieces of pixel data that are made up of m (m2) types of color components, m being smaller than n; a color component correcting means for correcting the converted pieces of pixel data made up of m types of color components with use of a predetermined color component correction coefficient; and an acquiring means for acquiring an evaluation result related to a target illness based on the corrected pieces of pixel data made up of m types of color components.

A technique for modifying a digital representation of a color, based on a given color palette.

In one or more embodiments, an image processing apparatus obtains a shade image representing shade components included in a multi-valued image obtained by capturing an image of a document. The shade components depend on an image capture environment. The apparatus binarizes a pixel value of a target pixel in the multi-valued image based on a pixel value of a corresponding pixel in the shade image at coordinates identical to those of the target pixel to generate a pixel value representing white or black. One or more image processing methods and storage mediums are also provided herein.

A real-time color mapping system includes a memory and a converting module. The memory is configured for storing a mapping table. The converting module is configured for reading the mapping table stored in the memory, and for converting first image grayscale values corresponding to a first image signal into second image grayscale values corresponding to a second image signal according to the mapping table. The converting module utilizes at least part of bits corresponding to each of the first image grayscale values as a memory address to look up in the mapping table, thereby converting the first image grayscale values into the second image grayscale values. A real-time color mapping method is provided herein as well.