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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. [1]
Better Portable Graphics (BPG) is a file format for coding digital images, which was created by programmer Fabrice Bellard in 2014. He has proposed it as a replacement for the JPEG image format as the more compression-efficient alternative in terms of image quality or file size. [1]
This category includes articles, which includes information on image compression methods and algorithms. For information on graphics file formats see Category:Graphics file formats . Subcategories
JavaScript and Cascading Style Sheet (CSS) resources may be minified, preserving their behavior while considerably reducing their file size. Libraries available online are capable of minification and optimization to varying degrees. Some libraries also merge multiple script files into a single file for client download.
Typically, compressions using lossless operation mode can achieve around 2:1 compression ratio for color images. [5] This mode is quite popular in the medical imaging field, and defined as an option in DNG standard, but otherwise it is not very widely used because of complexity of doing arithmetics on 10, 12, or 14bpp values on typical embedded 32-bit processor and a little resulting gain in ...
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.
Compressing drawings or diagrams with JPEG results in an image of poor quality, because the human eye can spot the compression artifacts around the edges. Another drawback is the large file size you will end up with. JPEG compression has many options but most commonly only two colour spaces: 24-bit RGB (8 bits per sample) and 8-bit greyscale.
Most lossless compression programs do two things in sequence: the first step generates a statistical model for the input data, and the second step uses this model to map input data to bit sequences in such a way that "probable" (i.e. frequently encountered) data will produce shorter output than "improbable" data.