In Computing, What is Zipping?

Compression is a mechanism that uses a specific algorithm to reduce the size of a computer's files. This mechanism is a very convenient invention, especially for network users, because it can reduce the total number of bytes of a file, enable faster file transmission through a slower Internet connection, and reduce the disk footprint of the file. space.

Compression is to reduce the data size to save storage space and transmission time. For data transmission, compression can be applied to individual data content or all transmission units (including data headers), depending on some specific factors.

Content compression is simple: it removes extra whitespace characters, inserts a single repeated character to indicate repeated characters in a string, and replaces small bit strings with frequently used characters. This type of compression can reduce the size of text files by 50%. Compression is performed by a program using specific formulas and algorithms that determine how to compress and decompress data. ^[1]

Algorithms are used to process files losslessly or losslessly so as to retain the most file information and reduce the file size.

There are two forms of duplication in computer data, and zip is the compression of these two types of duplication.

The first

One is a repetition in the form of a phrase, that is, a repetition of more than three bytes. For this kind of repetition, zip uses two numbers: 1. the distance between the repetition position and the current compression position; 2. the length of the repetition, which represents the repetition, Assuming these two numbers each occupy one byte, the data is compressed, which is easy to understand.

One byte has 256 possible values from 0 to 255, and three bytes have 256 * 256 * 256. There are more than 16 million possible cases. The possibility of longer phrase values grows exponentially It seems that the probability of repetition is extremely low, but it is not true. Various types of data have a tendency to repeat. In a paper, a few terms tend to repeat; a novel, the names of people and places will appear repeatedly; A gradient background image, pixels in the horizontal direction will repeat; the program's

Compression introduction

Image compression technology is a technology that compresses the amount of information when transmitting an image, and can still see the original image after restoration.

Uncompressed graphics, images, and audio data require very objective storage space. Even with optical disc storage technology, uncompressed video is often impractical. In the digital image monitoring system, a large amount of video data needs to be processed, so the compression encoding and decoding of the image is very important. Now there are many compression methods used in digital surveillance systems. Currently more commonly used are: JPEG (for a single image), H.261 (P × 64), MPEG (for video for video and audio). ^[2]

Compression Technology Classification

Image compression techniques can be classified into different types. For their application in multimedia systems, we can distinguish them by source, entropy and hybrid coding. Entropy coding is lossless coding, while source coding is lossy compression. Most multimedia systems use hybrid technology, that is, the two technologies are mixed together.

The use of entropy coding does not take into account the special properties of the media. The compression of the data stream is considered as a simple sequence of numbers, and the correlation of the data is not considered. Entropy coding is an example of lossless compression because the decompression process completely recovers the original data. Run-length encoding is an example of entropy encoding, which is often used as data compression for file systems.

Source coding takes into account the context of the data. The compression rate of the source encoding depends on the data content. For the lossy compression technology, there is a one-way relationship between the source data stream and the encoded data stream. The data streams are similar but not the same. Different source encoding techniques make full use of the characteristics of specific media. ^[2]