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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.
This category includes articles, which includes information on image compression methods and algorithms. For information on graphics file formats see Category: ...
Original file (5,184 × 3,888 pixels, file size: 8 MB, MIME type: image/jpeg) This is a file from the Wikimedia Commons . Information from its description page there is shown below.
In contrast, lossy compression (e.g. JPEG for images, or MP3 and Opus for audio) can achieve much higher compression ratios at the cost of a decrease in quality, such as Bluetooth audio streaming, as visual or audio compression artifacts from loss of important information are introduced.
Free Lossless Image Format (FLIF) is a lossless image format claiming to outperform PNG, lossless WebP, lossless BPG and lossless JPEG 2000 in terms of compression ratio on a variety of inputs. [ 4 ]
The Quite OK Image Format (QOI) is a specification for lossless image compression of 24-bit (8 bits per color RGB) or 32-bit (8 bits per color with 8-bit alpha channel RGBA) color raster (bitmapped) images, invented by Dominic Szablewski and first announced on 24 November 2021.
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.