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2. Lossless compression - Wikipedia

   en.wikipedia.org/wiki/Lossless_compression

   Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. Lossless compression is possible because most real-world data exhibits statistical redundancy . [ 1 ]

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. 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.

5. Lempel–Ziv–Markov chain algorithm - Wikipedia

   en.wikipedia.org/wiki/Lempel–Ziv–Markov_chain...

   This algorithm uses a dictionary compression scheme somewhat similar to the LZ77 algorithm published by Abraham Lempel and Jacob Ziv in 1977 and features a high compression ratio (generally higher than bzip2) [2] [3] and a variable compression-dictionary size (up to 4 GB), [4] while still maintaining decompression speed similar to other ...

6. Data compression ratio - Wikipedia

   en.wikipedia.org/wiki/Data_compression_ratio

   Thus, a representation that compresses the storage size of a file from 10 MB to 2 MB yields a space saving of 1 - 2/10 = 0.8, often notated as a percentage, 80%. For signals of indefinite size, such as streaming audio and video, the compression ratio is defined in terms of uncompressed and compressed data rates instead of data sizes:

7. Lossy compression - Wikipedia

   en.wikipedia.org/wiki/Lossy_compression

   Basic information theory says that there is an absolute limit in reducing the size of this data. When data is compressed, its entropy increases, and it cannot increase indefinitely. For example, a compressed ZIP file is smaller than its original, but repeatedly compressing the same file will not reduce the size to nothing. Most compression ...