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.

An image processing method includes determining whether image data acquired by reading a document with a reading unit is color or monochrome, saving color image data determined to be color and monochrome image data generated by monochrome conversion of the color image data, in association with each other as a learning sample, deciding a color conversion parameter to be used when image data read by the reading unit and determined to be monochrome image data is converted into a color image, using the saved learning sample, and converting the image data read by the reading unit and determined to be the monochrome image data into color image data, using the decided color conversion parameter.

An image processing apparatus comprises: an obtaining unit configured to obtain image data of an original read by a reading unit; a detection unit configured to detect an object from the image data; a color determination unit configured to determine whether an object detected by the detection unit is a color image or a monochrome image; a conversion unit configured to convert each object determined to be a monochrome image by the color determination unit into a color image; and a display unit configured to perform a display, for each object converted by the conversion unit, in which editing by a user is possible.

This document describes techniques and apparatuses for implementing monochrome-color mapping using a monochromatic imager and a color map sensor. These techniques and apparatuses enable better resolution, depth of color, or low-light sensitivity than many conventional sensor arrays.

Various techniques are provided to generate enhanced visual representations of captured infrared (IR) data values. For example, various methods, systems, devices, and machine-readable mediums are provided that may be used to map color and/or grayscale values to temperature values. Such mapping permits a user to intuitively interpret the temperatures associated with the IR data values. The temperatures may be presented as a visual representation of the captured IR data values having an enhanced contrast.

In a method and computer for visualizing a medical image data set, in particular a magnetic resonance image data set, the medical imaging data set is provided to the computer which determines a first subset of the medical image data set related to a first parameter and a second subset of the medical image data set related to a second parameter. A first color is assigned to the first subset and a second color is assigned to the second subset. The first subset is transferred to a display in a first color presentation using the first color and the second subset is transferred in a second color presentation using the second color. The first color presentation and the second color presentation are combined for visualizing the medical imaging data set.

There are disclosed methods and apparatus for enhancing the image exposure of image inventories. A frame conversion and packaging machine assigns metadata to each frame of a digital video work. It takes objects that have been detected, recognized and assigned metadata to the objects by the frame slicing and packaging machine and enhances the image exposure and assigns new items of metadata to the enhanced-exposure modified images. The frame conversion and packaging machine then generates a cryptographic hash of the enhanced-exposure modified image's digital file. The frame conversion and packaging machine writes the hash to a node of a transaction processing network. Further, there are disclosed methods and apparatus for conversion of monochromatic image inventories to colored image inventories. A frame color-conversion and packaging machine assigns metadata to each frame of a digital video work. It takes objects that have been detected, recognized and assigned metadata to the objects by the frame slicing and packaging machine and converts the original monochromatic images to fully colorized images and assigns new items of metadata to the color-converted images. The frame color-conversion and packaging machine then generates a cryptographic hash of the color-converted modified image's digital file. The frame color-conversion and packaging machine writes the hash to a node of a transaction processing network.

An image processing system according to the present disclosure includes: an image acquisition unit configured to acquire a monochrome image of a subject including a target part; a hint acquisition unit configured to acquire a category of the target part and a first color hint indicating a color of the target part; a hint conversion unit configured to convert the first color hint into a second color hint indicating the color of the target part based on the acquired category; and a colorization generation unit configured to generate a colorized image corresponding to the monochrome image from the monochrome image and the second color hint of the target part by using a prediction model trained by machine learning.

In an image data conversion device, color image data is represented in gray scale, a histogram of brightness values is created for the gray-scaled image data, it is determined based on the created histogram which image pattern of a plurality of image patterns the gray-scaled image data is classified into, a range subjected to gamma correction and a range fixed to at least one of a minimum value and a maximum value of gray scale are set for each image pattern, and image data conversion including the gamma correction is performed on the gray-scaled image data.

A digital encoding and decoding method of high bit-depth gray scale medical images allows standard 3-channel color image compression algorithms to be used to compress and de-compress such encoded high bit-depth gray scale images without significant image quality loss. The digital encoding and decoding method may be used to improve the network transmission, storage and rendering of such gray scale images in a standard web browser.