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A ezw data compression method based on random threshold adjustment

A technology of data compression and threshold adjustment, which is applied in digital video signal modification, image communication, electrical components, etc. It can solve problems such as compression quality degradation and signal-to-noise ratio degradation, and achieve high compression ratio, high compression ratio, and good restoration effect Effect

Active Publication Date: 2022-01-28
GUIZHOU UNIV
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Problems solved by technology

However, the compression quality will decrease and the signal-to-noise ratio will decrease

Method used

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  • A ezw data compression method based on random threshold adjustment
  • A ezw data compression method based on random threshold adjustment
  • A ezw data compression method based on random threshold adjustment

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Embodiment Construction

[0042] The present invention will be further introduced below in conjunction with the accompanying drawings and specific embodiments.

[0043] Embedded zerotree wavelet principle: multi-resolution analysis and wavelet transform, let x∈R,f:x→R and ψ k (x): x→R is a linearly independent function system, then f(x) can be expressed as:

[0044]

[0045] Among them, a k is the expansion coefficient, and V is called the function system {ψ k The spanning space of (x)}:

[0046]

[0047] For example, with integer translations and real binary scales, the square integrable function ψ k Form the set of expansion functions {ψ j,k (x)}:

[0048] The wavelet forward and inverse transform formulas of one-dimensional functions are as follows:

[0049]

[0050]

[0051] where C ψ Satisfying the admissible conditions, formula (3) is the process of finding the expansion coefficient, and formula (4) is a function in the spanning function space. Let the function system {ψ j,k ...

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Abstract

The invention discloses an EZW data compression method based on random threshold adjustment. The method includes the steps of performing wavelet encoding on an image as wavelet transform, quantization, and encoding. The decoding process is the opposite. When scanning and encoding an image, the initial threshold is calculated first. , and then carry out EZW encoding. EZW encoding adopts the method of randomly adjusting the threshold value for judging the importance of wavelet coefficients to encode the digital image. random number. The present invention randomly adjusts the threshold value for judging the importance of wavelet coefficients, and allows the threshold value to be randomly selected in a small range, so that the image can improve the compression ratio while ensuring the quality of restoration. For the same picture, the threshold value is randomly selected in different ranges for encoding. The compression ratio has been improved, and the restoration effect of the distorted compressed image is better. Although the peak signal-to-noise ratio has decreased to a certain extent, the effect is not significant.

Description

technical field [0001] The invention relates to an EZW data compression method based on random threshold adjustment, and belongs to the technical field of distributed power supply parallel operation control. Background technique [0002] The information displayed by the image is obvious, intuitive, and clear, and can well represent the information that people see. However, the image contains a large amount of information, which makes the image information occupy a large storage space and increases the cost of information acquisition. Nowadays, in the era of rapid development of the network, a large amount of information redundancy can no longer meet people's requirements for the speed of information acquisition. . In such an era environment, image compression has become an important direction for people to solve problems. Such as remote sensing images, medical images, meteorological cloud images, digital television and other fields have a wide range of applications. There...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N19/48H04N19/64
Inventor 谢玫秀马家庆
Owner GUIZHOU UNIV
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