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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]
Grayscale images are distinct from one-bit bi-tonal black-and-white images, which, in the context of computer imaging, are images with only two colors: black and white (also called bilevel or binary images). Grayscale images have many shades of gray in between. Grayscale images can be the result of measuring the intensity of light at each pixel ...
Ordered dithering is any image dithering algorithm which uses a pre-set threshold map tiled across an image. It is commonly used to display a continuous image on a display of smaller color depth. For example, Microsoft Windows uses it in 16-color graphics modes. The algorithm is characterized by noticeable crosshatch patterns in the result.
Floyd–Steinberg dithering is an image dithering algorithm first published in 1976 by Robert W. Floyd and Louis Steinberg. It is commonly used by image manipulation software. For example when converting an image from a Truecolor 24-bit PNG format into a GIF format, which is restricted to a maximum of 256 colors.
I420 is a simpler design and is more commonly used. The entire image in Y is written out, followed by the image in U, then by the whole image in V. I420 layout; YV12 follows the same general design as I420, only the order between the U and V images is flipped. [18] NV12 is possibly the most commonly-used 8-bit 4:2:0 format.
ImageMagick, invoked from the command line as magick, is a free and open-source [3] cross-platform software suite for displaying, creating, converting, modifying, and editing raster images. ImageMagick was created by John Cristy in 1987, it can read and write over 200 image file formats .
Learn how to download and install or uninstall the Desktop Gold software and if your computer meets the system requirements.
Without dithering, the colors in the original image would be quantized to the closest available color, resulting in a displayed image that is a poor representation of the original. The very earliest uses were to reduce images to 1-bit black and white. This may have been done for printing even earlier than for bit-mapped video graphics.
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