Image compression method combining wavelet packet transformation and singular value decomposition

A technology of singular value decomposition and wavelet packet transformation, applied in image coding, image data processing, instruments, etc., can solve the problems of image edge and texture distortion, limited direction, and unable to express the singularity characteristics of the image well, and achieve important The effect of structure quality improvement

Pending Publication Date: 2021-05-25
CHENGDU POLYTECHNIC
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Problems solved by technology

However, since the wavelet packet transform is a two-dimensional wavelet transform on the image, it is a tensor product of one-dimensional wavelet, and its direction is limited, which cannot express the singularity characteristics of the image well, so that the compressed image edge and textures may appear more noticeable distortion

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  • Image compression method combining wavelet packet transformation and singular value decomposition
  • Image compression method combining wavelet packet transformation and singular value decomposition

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Embodiment Construction

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0016] refer to figure 1 , the image compression method combining wavelet packet transform and singular value decomposition of the embodiment of the present invention comprises:

[0017] S1: Perform wavelet packet decomposition on the original image to obtain the complete binary tree of the original image.

[0018] Among them, the complete binary tree is a tree-shaped data structure, which has a parent node and child nodes of the parent node, and each node ca...

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Abstract

The invention discloses an image compression method combining wavelet packet transformation and singular value decomposition, which comprises the following steps of: performing wavelet packet decomposition on an original image to obtain a complete binary tree; taking logarithmic energy entropy as a cost function, sequentially and upwards comparing logarithmic energy entropy values of child nodes and father nodes from the bottom layer of the complete binary tree, retaining nodes with smaller logarithmic energy entropy values, deleting nodes with larger logarithmic energy entropy values, and further obtaining an optimal wavelet tree; reconstructing the optimal wavelet tree by adopting a wavelet packet reconstruction algorithm to obtain a reconstructed image; performing singular value decomposition on the two-dimensional time-frequency information of the reconstructed image to decompose the two-dimensional time-frequency information into texture vectors, geometric vectors and singular values; processing the data in an energy spectrum mode to obtain a characteristic value set; processing the feature value set by adopting a self-adaptive singular value decomposition method to obtain a singular value threshold number K, and selecting the first K feature values in the feature value set to form an approximate matrix; according to the invention, the image compression quality can be improved, and a high compression ratio can be obtained.

Description

technical field [0001] The invention relates to the technical field of image compression, in particular to an image compression method combining wavelet packet transformation and singular value decomposition. Background technique [0002] If a digital image file is not compressed, its data volume is relatively large, which has a relatively large adverse effect on storage and transmission. If you just need to browse the image quickly, you can use a lossy compression method to remove some non-key information from the image to reduce the amount of data. However, when high-quality images are required, the texture components and detail information of the image need to be preserved, and these high-frequency subbands containing texture and details need to be preserved when compressing the image, which limits the compression ratio of the image. [0003] Wavelet analysis theory is a fine analysis method. When using wavelet packet for image compression, a higher compression ratio can...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T9/40
CPCG06T9/007G06T9/40
Inventor 谢力
Owner CHENGDU POLYTECHNIC
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