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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.
JPEG-LS was developed with the aim of providing a low-complexity lossless and near-lossless image compression standard that could offer better compression efficiency than lossless JPEG. It was developed because at the time, the Huffman coding -based JPEG lossless standard and other standards were limited in their compression performance.
This is an accepted version of this page This is the latest accepted revision, reviewed on 31 December 2024. Lossy compression method for reducing the size of digital images For other uses, see JPEG (disambiguation). "JPG" and "Jpg" redirect here. For other uses, see JPG (disambiguation). JPEG A photo of a European wildcat with the compression rate, and associated losses, decreasing from left ...
JPEG XS is a light-weight compression that visually preserves the quality compared to an uncompressed stream, at a low cost, targeted at compression ratios of up to 10:1. With XS, it is for example possible to repurpose existing SDI cables to transport 4K60 over a single 3G-SDI (at 4:1), and even over a single HD-SDI (at 8:1).
Beamr was founded by Sharon Carmel, an entrepreneur with a background in image and video processing. [4] Beamr’s clients include companies like Netflix , Viacom CBS, and Snapfish . Its technology is backed by 53 internationally granted patents and was awarded a Technology and Engineering Emmy in 2021 .
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]