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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]
This characteristic sometimes results in a smaller file size for some lossless formats than lossy formats. For example, graphically simple images (i.e. images with large continuous regions like line art or animation sequences) may be losslessly compressed into a GIF or PNG format and result in a smaller file size than a lossy JPEG format.
Composite image showing JPG and PNG image compression. Left side of the image is from a JPEG image, showing lossy artefacts; the right side is from a PNG image. In the late 1980s, digital images became more common, and standards for lossless image compression emerged. In the early 1990s, lossy compression methods began to be widely used. [14]
Thus, a representation that compresses the storage size of a file from 10 MB to 2 MB yields a space saving of 1 - 2/10 = 0.8, often notated as a percentage, 80%. For signals of indefinite size, such as streaming audio and video, the compression ratio is defined in terms of uncompressed and compressed data rates instead of data sizes:
An archive format designed for the Apple II series of computers. The canonical implementation is ShrinkIt, which can operate on disk images as well as files. Preferred compression algorithm is a combination of RLE and 12-bit LZW. Archives can be manipulated with the command-line NuLib tool, or the Windows-based CiderPress. .sit application/ x ...
A lossless compression algorithm is useful only when we are more likely to compress certain types of files than others; then the algorithm could be designed to compress those types of data better. Thus, the main lesson from the argument is not that one risks big losses, but merely that one cannot always win.
Smallpdf is a Swiss online web-based PDF software, founded in 2013. [2] It offers free version with limited features to compress, convert and edit PDF documents. [3] And its paid version offers advanced features like OCR, compress, and more. [4]
While data reduction (compression, be it lossy or lossless) is a main goal of transform coding, it also allows other goals: one may represent data more accurately for the original amount of space [5] – for example, in principle, if one starts with an analog or high-resolution digital master, an MP3 file of a given size should provide a better ...