Lossless compression: Difference between revisions

Latest revision as of 16:56, 29 December 2024

Data compression technique

Lossless compression is a class of data compression algorithms that allows the original data to be perfectly reconstructed from the compressed data. In contrast, lossy compression permits some loss of data, which may not be recoverable.

Overview[edit]

Lossless compression is used in many applications where it is important that the original and the decompressed data be identical. Typical examples are executable programs, text files, and source code. Some image file formats, like PNG or GIF, use only lossless compression, while others like JPEG use both lossless and lossy methods.

Techniques[edit]

Lossless compression algorithms exploit statistical redundancy to represent data more concisely without losing information. Common techniques include:

Applications[edit]

Lossless compression is crucial in fields such as medical imaging, where the loss of any data could affect the diagnosis. Formats like DICOM use lossless compression to ensure that medical images are preserved without any loss of detail.

Comparison with Lossy Compression[edit]

While lossless compression is essential for certain types of data, lossy compression is often used for multimedia data such as audio, video, and images, where a perfect reproduction is not necessary. Lossy compression can achieve much higher compression ratios than lossless methods.

References[edit]

External links[edit]

Lossless compression on Wikipedia

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-[[File:for_example,_lossless_audio_compression_programs_do_not_work_well_on_text_files,_and_vice_versa.|thumb|for_example,_lossless_audio_compression_programs_do_not_work_well_on_text_files,_and_vice_versa.]] '''Lossless compression'''
-'''Lossless compression''' is a class of [[data compression]] algorithms that allows the original data to be perfectly reconstructed from the compressed data. Unlike [[lossy compression]], which permits some loss of data, lossless compression ensures that all the original information is preserved.
+{{Short description|Data compression technique}}
+{{Use dmy dates|date=October 2023}}
+{{Infobox compression method
+| name = Lossless compression
+| title = Lossless data compression
+| image = <!-- Image removed -->
+| caption = Example of lossless data compression
+| genre = Data compression
+}}
-==Overview==
+'''Lossless compression''' is a class of [[data compression]] algorithms that allows the original data to be perfectly reconstructed from the compressed data. In contrast, [[lossy compression]] permits some loss of data, which may not be recoverable.
-Lossless compression is widely used in various applications where it is crucial to retain the original data without any loss. This includes text files, executable files, and certain types of image and audio files. The primary goal of lossless compression is to reduce the size of data without compromising its integrity.
-==Techniques==
+== Overview ==
-Several techniques are employed in lossless compression, including:
+Lossless compression is used in many applications where it is important that the original and the decompressed data be identical. Typical examples are [[executable]] programs, [[text file]]s, and [[source code]]. Some image file formats, like [[Portable Network Graphics|PNG]] or [[Graphics Interchange Format|GIF]], use only lossless compression, while others like [[Joint Photographic Experts Group|JPEG]] use both lossless and lossy methods.
+== Techniques ==
+Lossless compression algorithms exploit statistical redundancy to represent data more concisely without losing information. Common techniques include:
 * [[Run-length encoding]] (RLE)
 * [[Huffman coding]]
-* [[Lempel-Ziv-Welch]] (LZW)
+* [[Lempel–Ziv–Welch]] (LZW)
-* [[Arithmetic coding]]
+* [[Burrows–Wheeler transform]]
-* [[Burrows-Wheeler transform]] (BWT)
-Each of these methods has its own advantages and is chosen based on the specific requirements of the data being compressed.
+== Applications ==
+Lossless compression is crucial in fields such as [[medical imaging]], where the loss of any data could affect the diagnosis. Formats like [[DICOM]] use lossless compression to ensure that medical images are preserved without any loss of detail.
-===Run-length encoding===
+== Comparison with Lossy Compression ==
-Run-length encoding is one of the simplest forms of lossless compression. It works by reducing the physical size of a repeating string of characters. For example, the string "AAAAA" would be encoded as "5A".
+While lossless compression is essential for certain types of data, lossy compression is often used for [[multimedia]] data such as [[audio]], [[video]], and [[images]], where a perfect reproduction is not necessary. Lossy compression can achieve much higher compression ratios than lossless methods.
-===Huffman coding===
+== See also ==
-Huffman coding is a popular method that uses variable-length codes to represent symbols based on their frequencies. Symbols that occur more frequently are assigned shorter codes, while less frequent symbols are assigned longer codes.
+* [[Data compression]]
+* [[Entropy encoding]]
-===Lempel-Ziv-Welch===
+* [[Information theory]]
-Lempel-Ziv-Welch is a dictionary-based compression algorithm. It works by replacing repeated occurrences of data with references to a single copy of that data existing earlier in the uncompressed data stream.
-===Arithmetic coding===
-Arithmetic coding is a form of entropy encoding used in lossless data compression. It represents a sequence of symbols as a single number between 0 and 1. The more frequently a symbol appears, the smaller the range it occupies.
-===Burrows-Wheeler transform===
-The Burrows-Wheeler transform is a block-sorting algorithm that rearranges a string of characters into runs of similar characters. This makes the data more amenable to compression by other algorithms.
-==Applications==
-Lossless compression is used in various fields, including:
-* [[File compression]] (e.g., [[ZIP (file format)|ZIP]], [[Gzip]])
-* [[Image compression]] (e.g., [[Portable Network Graphics|PNG]], [[Graphics Interchange Format|GIF]])
-* [[Audio compression]] (e.g., [[Free Lossless Audio Codec|FLAC]], [[Apple Lossless|ALAC]])
-* [[Data transmission]] and storage
-==Advantages and Disadvantages==
-===Advantages===
-* No loss of data: The original data can be perfectly reconstructed.
-* Versatility: Suitable for a wide range of data types.
-===Disadvantages===
+== References ==
-* Lower compression ratios compared to lossy compression.
+{{Reflist}}
-* Computationally intensive: Some algorithms require significant processing power.
-==Related Pages==
+== External links ==
-* [[Data compression]]
+* [https://en.wikipedia.org/wiki/Lossless_compression Lossless compression on Wikipedia]
-* [[Lossy compression]]
-* [[Entropy encoding]]
-* [[File format]]
-* [[Compression algorithm]]
-==Categories==
 [[Category:Data compression]]
 [[Category:Computer science]]
+[[Category:Information theory]]
-{{Data-compression-stub}}