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  2. Image compression - Wikipedia

    en.wikipedia.org/wiki/Image_compression

    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.

  3. Quantization (image processing) - Wikipedia

    en.wikipedia.org/wiki/Quantization_(image...

    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.

  4. Wikipedia:Preparing images for upload - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Preparing_images...

    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.

  5. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    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]

  6. Category:Image compression - Wikipedia

    en.wikipedia.org/wiki/Category:Image_compression

    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

  7. PAQ - Wikipedia

    en.wikipedia.org/wiki/PAQ

    It does include models for color BMP, TIFF and JPEG files, so compresses these files better. The primary difference from PAQ6 is it uses a neural network to combine models rather than a gradient descent mixer. Another feature is PAQ7's ability to compress embedded jpeg and bitmap images in Excel-, Word- and pdf-files.

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