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  2. Lossy compression - Wikipedia

    en.wikipedia.org/wiki/Lossy_compression

    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 ...

  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. 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.

  5. Lossless JPEG - Wikipedia

    en.wikipedia.org/wiki/Lossless_JPEG

    IrfanView image viewer and editor has full read+write support for JPEG-LS image codec (.jls file extension). XnView image viewer and editor claims the capability to read JPEG-LS (.jls) files. However, XnViewMP v0.98.1 can not read JPEG-LS files created by IrfanView v4.54. CharLS - an open-source JPEG-LS codec.

  6. Image file format - Wikipedia

    en.wikipedia.org/wiki/Image_file_format

    JPEG XL is a royalty-free raster-graphics file format that supports both lossy and lossless compression. It supports reversible recompression of existing JPEG files, as well as high-precision HDR (up to 32-bit floating point values per pixel component). It is designed to be usable for both delivery and authoring use cases.

  7. 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.

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