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  2. Reducing PDF file size with a Quartz filter - Engadget

    www.engadget.com/2007-12-12-reducing-pdf-file...

    Apple has an interesting video tip up this week on reducing the file size of graphic intensive PDFs created from the Print dialog. In their example they make a PDF from a Keynote presentation ...

  3. Smallpdf.com - Wikipedia

    en.wikipedia.org/wiki/Smallpdf.com

    The initial version of the site featured a standalone PDF compression tool. [5] Since then, the online platform has introduced over 16 PDF tools to convert, compress and edit PDF documents. [ 6 ] As of 2019, approximately 25 million unique users use Smallpdf every month.

  4. Image compression - Wikipedia

    en.wikipedia.org/wiki/Image_compression

    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 ...

  5. Sumatra PDF - Wikipedia

    en.wikipedia.org/wiki/Sumatra_PDF

    The Sumatra PDF Viewer is a tiny open source portable reader that opens PDF's in the blink of an eye. Bloat and startup time is a major drawback to Adobe Reader, so we fled to the faster arms of Foxit Reader long ago. However, at 850KB, Sumatra is way slimmer than FoxIt. ^ Anders Ingeman Rasmussen (2008).

  6. Lossy compression - Wikipedia

    en.wikipedia.org/wiki/Lossy_compression

    In information technology, lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content. These techniques are used to reduce data size for storing, handling, and transmitting content. The different versions of the photo of the cat on ...

  7. 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.

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