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2. DjVu - Wikipedia

   en.wikipedia.org/wiki/DjVu

   DjVu has been promoted as providing smaller files than PDF for most scanned documents. [3] The DjVu developers report that color magazine pages compress to 40–70 kB, black-and-white technical papers compress to 15–40 kB, and ancient manuscripts compress to around 100 kB; a satisfactory JPEG image typically requires 500 kB. [4]

3. bzip2 - Wikipedia

   en.wikipedia.org/wiki/Bzip2

   bzip2 compresses data in blocks between 100 and 900 kB and uses the Burrows–Wheeler transform to convert frequently recurring character sequences into strings of identical letters. The move-to-front transform and Huffman coding are then applied. The compression performance is asymmetric, with decompression being faster than compression.

4. 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].

5. Data compression ratio - Wikipedia

   en.wikipedia.org/wiki/Data_compression_ratio

   Lossless compression of digitized data such as video, digitized film, and audio preserves all the information, but it does not generally achieve compression ratio much better than 2:1 because of the intrinsic entropy of the data. Compression algorithms which provide higher ratios either incur very large overheads or work only for specific data ...

6. List of archive formats - Wikipedia

   en.wikipedia.org/wiki/List_of_archive_formats

   Genozip, a compressor for genomic file formats such as FASTQ, BAM, VCF and others. [4].gz application/gzip [5] gzip: Unix-like GNU Zip, the primary compression format used by Unix-like systems. The compression algorithm is Deflate, which combines LZSS with Huffman coding. .lz application/x-lzip lzip: Unix-like

7. Lossless compression - Wikipedia

   en.wikipedia.org/wiki/Lossless_compression

   Most lossless compression programs do two things in sequence: the first step generates a statistical model for the input data, and the second step uses this model to map input data to bit sequences in such a way that "probable" (i.e. frequently encountered) data will produce shorter output than "improbable" data.