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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.
WebP is an open image format released in 2010 that uses both lossless and lossy compression. It was designed by Google to reduce image file size to speed up web page loading: its principal purpose is to supersede JPEG as the primary format for photographs on the web. WebP is based on VP8's intra-frame coding and uses a container based on RIFF.
WebP is a raster graphics file format developed by Google intended as a replacement for JPEG, PNG, and GIF file formats. It supports both lossy and lossless compression, [8] as well as animation and alpha transparency.
WebP: WebP image format Google.webp image/webp General purpose royalty-free WMF: Windows Metafile Format Microsoft.wmf, .wmz XAR: Xar Xara: Xar (graphics).xar application/vnd.xara Xara Photo & Graphic Designer: Yes XBM: X BitMap, colour variant of original black-and-white bitmap (bmp) format .xbm, .bm,.icon, .bitmap image/x-xbitmap
This is because uncompressed audio can only reduce file size by lowering bit rate or depth, whereas compressing audio can reduce size while maintaining bit rate and depth. This compression becomes a selective loss of the least significant data, rather than losing data across the board.
Continuously varied JPEG compression (between Q=100 and Q=1) for an abdominal CT scan. JPEG (/ ˈ dʒ eɪ p ɛ ɡ / JAY-peg, short for Joint Photographic Experts Group and sometimes retroactively referred to as JPEG 1) [2] [3] is a commonly used method of lossy compression for digital images, particularly for those images produced by digital photography.
If the compressor cannot store enough data in the compressed version, the result is a loss of quality, or introduction of artifacts. The compression algorithm may not be intelligent enough to discriminate between distortions of little subjective importance and those objectionable to the user.
Lossless compression methods may be categorized according to the type of data they are designed to compress. While, in principle, any general-purpose lossless compression algorithm ( general-purpose meaning that they can accept any bitstring) can be used on any type of data, many are unable to achieve significant compression on data that are ...