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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. Smallpdf.com - Wikipedia

    en.wikipedia.org/wiki/Smallpdf.com

    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 ] .

  4. Lossy compression - Wikipedia

    en.wikipedia.org/wiki/Lossy_compression

    The compression ratio (that is, the size of the compressed file compared to that of the uncompressed file) of lossy video codecs is nearly always far superior to that of the audio and still-image equivalents. Video can be compressed immensely (e.g., 100:1) with little visible quality loss

  5. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    Data compression aims to reduce the size of data files, enhancing storage efficiency and speeding up data transmission. K-means clustering, an unsupervised machine learning algorithm, is employed to partition a dataset into a specified number of clusters, k, each represented by the centroid of its points.

  6. Quantization (image processing) - Wikipedia

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

    When the number of discrete symbols in a given stream is reduced, the stream becomes more compressible. For example, reducing the number of colors required to represent a digital image makes it possible to reduce its file size. Specific applications include DCT data quantization in JPEG and DWT data quantization in JPEG 2000.

  7. Lossless compression - Wikipedia

    en.wikipedia.org/wiki/Lossless_compression

    In fact, if we consider files of length N, if all files were equally probable, then for any lossless compression that reduces the size of some file, the expected length of a compressed file (averaged over all possible files of length N) must necessarily be greater than N. [citation needed] So if we know nothing about the properties of the data ...

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