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What can be divided into data compression technologies? I believe that many inexperienced people are at a loss about this, so this article summarizes the causes and solutions of the problem. Through this article, I hope you can solve this problem.

Data compression technologies are divided into three categories, as follows:

1. Instant compression and non-instant compression

Real-time compression is to convert voice signals into digital signals, compress them at the same time, and then transmit them immediately through Internet. Real-time compression is generally used in video and sound data transmission.

Non-instant compression is carried out only when necessary and there is no real-time compression. Non-instant compression generally does not need special equipment, just install and use the corresponding compression software in the computer.

2. Digital compression and file compression

Digital compression refers to some time-bound data, which are often collected, processed or transmitted in real time.

File compression refers to the compression of data that will be stored in physical media such as disk, such as an article data, a section of music data, a section of program-encoded data and so on.

3. Lossless compression and lossy compression

Lossless compression uses the statistical redundancy of data for compression, so the compression ratio of lossless compression is generally low. This kind of method is widely used in the compression of text data, programs and image data in special applications.

The lossy compression method makes use of the characteristics that human vision and hearing are insensitive to some frequency components of image and sound, and allows the loss of certain information in the process of compression. Lossy compression is widely used in voice, image and video data compression.

After reading the above, have you mastered the methods that data compression technology can be divided into? If you want to learn more skills or want to know more about it, you are welcome to follow the industry information channel, thank you for reading!

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