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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.
Compression of an image to reduce file size (in Kb) is usually "lossy" and is not advised for featured pictures. Image compression will reduce download times and save disk space, but it does so at the expense of fine detail and overall image quality. If in doubt, when saving JPEG files, always select the "maximum" quality setting.
JPEG 2000 (JP2) is an image compression standard and coding system. It was developed from 1997 to 2000 by a Joint Photographic Experts Group committee chaired by Touradj Ebrahimi (later the JPEG president), [1] with the intention of superseding their original JPEG standard (created in 1992), which is based on a discrete cosine transform (DCT), with a newly designed, wavelet-based method.
Quantization, involved in image processing, is a lossy compression technique achieved by compressing a range of values to a single quantum (discrete) value. When the number of discrete symbols in a given stream is reduced, the stream becomes more compressible.
JPEGmini is a photo compression tool developed by Beamr Imaging Ltd released in 2012 for Mac and Windows.It designed to reduce the file size of images and videos with limited quality reduction. [1] [2] [3]
Guetzli supports only the top of JPEG's quality range (quantizer settings 84–100) [7] [8] and supports only sequential (non-"progressive") encoding. Guetzli is more effective with bigger files. [8] Google says it is a demonstration of the potential of psychovisual optimizations, intended to motivate further research into future JPEG encoders. [2]
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