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What is the main purpose of image data compression

青灯夜游
Release: 2022-07-04 15:34:05
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The main purpose of image data compression is to "reduce storage space". Image data compression cannot improve the clarity, contrast and brightness of the image, but image data compression can reduce storage space and increase the transmission speed of image data; compressing the image data to be stored under conditions that allow fidelity can greatly save storage space, and also greatly reduces the channel capacity during image transmission.

What is the main purpose of image data compression

The operating environment of this tutorial: Windows 7 system, Dell G3 computer.

The main purpose of image data compression is toreduce storage space.

With the rapid development of computer technology and network communication technology, real-time visual communication, multimedia communication, Internet TV, video surveillance and other services have attracted more and more attention. In this way, image compression technology has become an urgent problem to be solved.

Image data compression cannot improve the clarity, contrast and brightness of the image, but image data compression can reduce storage space and increase the transmission speed of image data.

Image compression is the basis for image storage, processing and transmission. It uses as little data as possible to store and transmit images. Image data can be compressed, which supports this theoretical basis and allows certain distortion in image encoding; redundancy of image data.

In most cases, the compressed image is not required to be exactly the same as the original image, but a small amount of distortion is allowed, as long as these distortions are not noticed by the human eye. This provides favorable conditions for improving the compression ratio. The more distortion that is allowed, the higher the compression efficiency that can be achieved. Because image data is compressible, there is a large amount of so-called statistical redundancy, which results in physiological visual redundancy. Removing this part of the image data does not affect the visual image quality, and even removing some image details has a negative impact on the actual image. Quality has no fatal impact either.

Because of this, the image data to be stored can be compressed under conditions that allow fidelity, greatly saving storage space, and also greatly reducing the channel capacity during image transmission. The development of optical disc technology and data compression technology provides technical guarantees for the transmission of large amounts of data in various forms, and the continuous improvement of CPU performance also provides favorable conditions for data compression.

Image compression technology

Image compression technology is divided into static compression and dynamic compression. JPEG is the first international standard for digital image compression. JPEG (Joint PhotographicExperts Group, Joint Photographic Experts Group) contains two basic compression methods:

(1) Lossy compression, also called distortion-free compression, is It means that the decompressed and restored data is exactly the same as the original data. The characteristic of this kind of compression is that the compression is relatively small.

It is a compression method based on adaptive discrete cosine transform DCT. The so-called lossy compression means that some information of the image will be lost after compression.

(2) Lossless compression, also called distortional compression, this kind of compression causes part of the information to be lost after compression, that is, there is an error between the restored data and the original data. It is characterized by a large compression ratio, and the compression ratio is adjustable from several times to hundreds of times.

Because its compression ratio has a certain limit, it is no longer a research hotspot. It is a compression method based on differential pulse code modulation DPCM.

Commonly used image data compression methods

Commonly used image data compression methods mainly include Huffman coding, run-length coding, arithmetic coding, discrete cosine transform coding and hybrid coding wait.

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