blocks|key|1388134|text|Huffman广泛应用于您可能遇到的所有主流压缩格式--从GZIP、PKZIP+(winzip等)和BZIP2到图像格式(如JPEG和PNG+)。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1388135|所有压缩方案都有病态的数据集，无法进行有意义的压缩；我上面列出的归档格式只是在遇到这些文件时“存储”未压缩的文件。|1388136|较新的算术距离编码方案往往因为专利问题而被避免，这意味着赫夫曼仍然是压缩行业的工作马。|offset|length|1388137|entityMap|0|LINK|mutability|MUTABLE|url|http://en.wikipedia.org/wiki/Arithmetic_coding|1|http://en.wikipedia.org/wiki/Arithmetic_coding#US_patents_on_arithmetic_coding^0|0|0|3|6|0|F|4|1|0^^$0|@$1|2|3|4|5|6|7|R|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|S|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|T|8|@]|9|@$F|U|G|V|1|W]|$F|X|G|Y|1|Z]]|A|$]]|$1|H|3|-4|5|6|7|10|8|@]|9|@]|A|$]]]|I|$J|$5|K|L|M|A|$N|O]]|P|$5|K|L|M|A|$N|Q]]]]

Huffman is widely used in all the mainstream compression formats that you might encounter - from GZIP, PKZIP (winzip etc) and BZIP2, to image formats such as JPEG and PNG.

All compression schemes have pathological data-sets that cannot be meaningfully compressed; the archive formats I listed above simply 'store' such files uncompressed when they are encountered.

Newer <a href="http://en.wikipedia.org/wiki/Arithmetic_coding" rel="noreferrer">arithmetic and range coding</a> schemes are often avoided because of <a href="http://en.wikipedia.org/wiki/Arithmetic_coding#US_patents_on_arithmetic_coding" rel="noreferrer">patent issues</a>, meaning Huffman remains the work-horse of the compression industry.

blocks|key|1388051|text|参见维基百科关于这一主题的文章：|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1388052|今天，Huffman编码经常被用作其他压缩方法的“后端”。压缩(PKZIP算法)和多媒体编解码，如JPEG和MP3，有一个前端模型和量化，然后是Huffman编码。|blockquote|1388053|entityMap|0|LINK|mutability|MUTABLE|url|http://en.wikipedia.org/wiki/Huffman_coding#Applications^0|2|4|0|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@]|9|@$A|P|B|Q|1|R]]|C|$]]|$1|D|3|E|5|F|7|S|8|@]|9|@]|C|$]]|$1|G|3|-4|5|6|7|T|8|@]|9|@]|C|$]]]|H|$I|$5|J|K|L|C|$M|N]]]]

See <a href="http://en.wikipedia.org/wiki/Huffman_coding#Applications" rel="noreferrer">Wikipedia</a> article on the subject:

<blockquote>
 Huffman coding today is often used as a "back-end" to some other compression method. DEFLATE (PKZIP's algorithm) and multimedia codecs such as JPEG and MP3 have a front-end model and quantization followed by Huffman coding.
</blockquote>

blocks|key|1388232|text|赫夫曼编码在现实世界中有很多应用.ZIP可能是使用最广泛的压缩工具，它使用Huffman编码作为其基础。谷歌上个月发布的最有效的无损压缩算法Brotli压缩算法也使用了Huffman编码。除此之外，Brotli还使用LZ77和其他一些基本的无损压缩算法。请参阅布罗蒂。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1388233|entityMap|0|LINK|mutability|MUTABLE|url|http://github.com/google/brotli^0|3M|4|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

There are quite a lot of real-world applications of Huffman Encoding. ZIP is perhaps the most widely used compression tool that uses Huffman Encoding as its basis. The latest of the most efficient lossless compression algorithms, Brotli Compression, released by Google last month also uses Huffman Coding. Apart from that, Brotli also uses LZ77 and a few other fundamental lossless compression algorithms. Refer to <a href="http://github.com/google/brotli" rel="nofollow">Brotli.</a>

blocks|key|1388170|text|当考虑压缩算法时，每种算法都有其优点和缺点。在给定一组输入的情况下，压缩的本质是对该数据存在着越来越好的压缩算法。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1388171|赫夫曼非常非常擅长某些事情。最值得注意的是，数据重复了很多次，并且包含了字符空间的子集。例如，英文文本文件。英语往往有相同的字母和相同的其他字母。|1388172|如果你的教授或书给你的印象是赫夫曼没有被使用，他们是错误的。例如，几乎所有与互联网的通信都是在某个时候被编码的。(一些通信协议使用它)。大多数图像文件(jpegs)都是哈夫曼编码的。大多数音乐文件(mp3s)都是赫夫曼编码的。还有许多其他的例子。|1388173|赫夫曼之所以被使用，是因为它可以通过一种名为自适应赫夫曼(+adaptive+)的稍微不同的算法被“发现”。当您阅读该文件时，您将学习Huffman代码和“压缩随走”。这是一个简单的概述，但你明白了。|1388174|为了解决情况问题的最佳算法，压缩文件允许使用许多不同的压缩，这取决于给定文件的最佳压缩。|1388175|entityMap^0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|M|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|N|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|O|8|@]|9|@]|A|$]]|$1|H|3|I|5|6|7|P|8|@]|9|@]|A|$]]|$1|J|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|K|$]]

When one considers compression algorithms there are often benefits and disadvantages to each. It is the nature of compression that given a set of input, there exists better and worse compression algorithms for that data.

Huffman is really, really good at some things. Most notably with data that repeats order a lot and contains a sub-set of the character space. For example english language text files. The english language tends to have the same letters followed by the same other letters.

If your professor or book gave you the impression that Huffman is not used, they are wrong. For example almost all communications with and from the internet are at some point Huffman encoded. (A number of communication protocols use it.) Most image files (jpegs) are Huffman encoded. Most music files (mp3s) are Huffman encoded. There are many other examples.

One reason Huffman is used is because it can be "discovered" via a slightly different algorithm called adaptive Huffman. As you read the file you learn the Huffman code and "compress as you go". This is a simplified overview , but you get the idea.

To solve the use the best algorithm for the situation problem, zip files allow a number of different compressions to be used depending on what the best one is for a given file.

blocks|key|1224989|text|HPACK中的字符串编码是一个非常广泛的应用，它是报头压缩+http/2的技术。|type|unstyled|depth|inlineStyleRanges|offset|length|style|BOLD|entityRanges|data|1224990|RFC确实直接提供了一个为压缩headers而优化的赫夫曼码表。|1224991|entityMap|0|LINK|mutability|MUTABLE|url|https://www.rfc-editor.org/rfc/rfc7541#section-5.2|1|https://www.rfc-editor.org/rfc/rfc7541#appendix-B^0|U|6|P|4|0|0|Q|5|1|0^^$0|@$1|2|3|4|5|6|7|R|8|@$9|S|A|T|B|C]]|D|@$9|U|A|V|1|W]]|E|$]]|$1|F|3|G|5|6|7|X|8|@]|D|@$9|Y|A|Z|1|10]]|E|$]]|$1|H|3|-4|5|6|7|11|8|@]|D|@]|E|$]]]|I|$J|$5|K|L|M|E|$N|O]]|P|$5|K|L|M|E|$N|Q]]]]

A very widespread application is the encoding of strings in HPACK, the <a href="https://www.rfc-editor.org/rfc/rfc7541#section-5.2" rel="nofollow noreferrer">header compression</a> technique of http/2.
The RFC does directly provide a <a href="https://www.rfc-editor.org/rfc/rfc7541#appendix-B" rel="nofollow noreferrer">Huffman Code Table</a> that is optimized for compressing HTTP headers.

blocks|key|1388181|text|Huffman码用于将固定长度码转换成可变长度码，从而实现无损压缩。可以使用JPEG和MPEG技术进一步压缩可变长度代码，以获得所需的压缩比。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1388182|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

Huffman code is used to convert fixed length codes into varible length codes, which results in lossless compression. Variable length codes may be further compressed using JPEG and MPEG techniques to get the desired compression ratio.

I am told that Huffman coding is used as loseless data compression algorithm, but I am also told that real data compress software do not employ Huffman coding, because if the keys are not distributed decentralized enough, the compressed file could be even larger than the orignal file.

This leaves me wondering are there any real-world application of Huffman coding?

What are the real-world applications of huffman coding?

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

文章

问答

视频

学习中心

腾讯云实验室

直播

竞赛

腾讯云代码分析专区

腾讯iOA零信任安全管理系统专区

腾讯云架构师技术同盟交流圈

腾讯云数据库专区

腾讯云顾问专区

腾讯云原生专区

腾讯混元专区

腾讯云TCE专区

腾讯云Lighthouse专区

腾讯云HAI专区

腾讯云Edgeone专区

腾讯云存储专区

腾讯云智能专区

腾讯轻联专区 

腾讯云开发专区

TAPD专区

腾讯轻量云游戏服专区

腾讯云最具价值专家

腾讯云架构师技术同盟

腾讯云创作之星

腾讯云开发者先锋

腾讯云代码助手

云原生构建

TAPD 敏捷项目管理

Cloud Studio

SDK中心

API中心

命令行工具

涵盖代码开发、场景应用、自动测试全流程，助你从零构建专属AI助手

一站式MCP教程库，解锁AI应用新玩法

我被告知，Huffman编码被用作无丢失的数据压缩算法，但我也被告知，真正的数据压缩软件不使用Huffman编码，因为如果密钥分布不够分散，压缩文件甚至可能比原始文件还要大。这让我想知道在现实世界中是否有赫夫曼编码的应用？

问赫夫曼编码的实际应用是什么？
EN

回答 6

Stack Overflow用户

Stack Overflow用户

Stack Overflow用户

社区

活动

圈层

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问赫夫曼编码的实际应用是什么？EN

回答 6

Stack Overflow用户

Stack Overflow用户

Stack Overflow用户

社区

活动

圈层

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问赫夫曼编码的实际应用是什么？
EN