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A 32-bit CMYK image (the industry standard as of 2005) is made of four 8-bit channels, one for cyan, one for magenta, one for yellow, and one for key color (typically is black). 64-bit storage for CMYK images (16-bit per channel) is not common, since CMYK is usually device-dependent, whereas RGB is the generic standard for device-independent ...
The number of channels depends on whether the image is grayscale or color and whether it has an alpha channel. PNG allows the following combinations of channels, called the color type. A demonstration of the color depth in a PNG file, in bits per channel. Left: 8 bits; Right: 16 bits. Note the artifacts, adjusted contrast for clarity.
According to this notion of a channel, color channels of an image can be redefined as output images that are obtained by extracting one specific color information point from the input image at a time. Similarly, a channel for a grayscale input image is simply equal to a grayscale input image.
For example, if an image contains 10 colors but has a color palette of 256 entries (8-bit), pngcrush can be used to reduce the color palette to a 4-bit one and truncate the palette to 10 entries. pngcrush can also change the color type of the image. For a true-color image, changing the color type from 2 to 0 converts it to greyscale.
Python Imaging Library is a free and open-source additional library for the Python programming language that adds support for opening, manipulating, and saving many different image file formats. It is available for Windows, Mac OS X and Linux. The latest version of PIL is 1.1.7, was released in September 2009 and supports Python 1.5.2–2.7. [3]
Image color transfer is a function that maps (transforms) the colors of one (source) image to the colors of another (target) image. A color mapping may be referred to as the algorithm that results in the mapping function or the algorithm that transforms the image colors.
Composite image showing JPG and PNG image compression. Left side of the image is from a JPEG image, showing lossy artefacts; the right side is from a PNG image. In the late 1980s, digital images became more common, and standards for lossless image compression emerged. In the early 1990s, lossy compression methods began to be widely used. [14]
Many of the techniques of digital image processing, or digital picture processing as it often was called, were developed in the 1960s, at Bell Laboratories, the Jet Propulsion Laboratory, Massachusetts Institute of Technology, University of Maryland, and a few other research facilities, with application to satellite imagery, wire-photo standards conversion, medical imaging, videophone ...