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Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data.
Magick image file format ImageMagick Studio .miff ImageMagick: MRW: Minolta RAW Minolta.mrw ORF: Olympus RAW Olympus: TIFF .orf PAM: portable arbitrary map file format .pam image/x-portable-arbitrarymap Yes PBM: Portable Bitmap File Format ASCII.pbm image/x-portable-bitmap Yes PCX: ZSoft PC Paintbrush File ZSoft Corporation.pcx, .pcc, .dcx ...
RGBE allows pixels to have the dynamic range and precision of floating-point values in a relatively compact data structure (32 bits per pixel) - often when images are generated from light simulations, the range of per-pixel color intensity values are much greater than will nicely fit into the standard 0..255 (8-bit) range of standard 24-bit image formats.
An image file format is a file format for a digital image. There are many formats that can be used, such as JPEG, PNG, and GIF. Most formats up until 2022 were for storing 2D images, not 3D ones. The data stored in an image file format may be compressed or uncompressed.
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]
DCT is the basis for JPEG, a lossy compression format which was introduced by the Joint Photographic Experts Group (JPEG) in 1992. [35] JPEG greatly reduces the amount of data required to represent an image at the cost of a relatively small reduction in image quality and has become the most widely used image file format.
The first alpha version of OpenCV was released to the public at the IEEE Conference on Computer Vision and Pattern Recognition in 2000, and five betas were released between 2001 and 2005. The first 1.0 version was released in 2006. A version 1.1 "pre-release" was released in October 2008. The second major release of the OpenCV was in October 2009.
Some picture formats allow an image's intended gamma (of transformations between encoded image samples and light output) to be stored as metadata, facilitating automatic gamma correction. The PNG specification includes the gAMA chunk for this purpose [ 14 ] and with formats such as JPEG and TIFF the Exif Gamma tag can be used.