Image processing method based on group-wave transformation compressed sensing

A processing method and compressed sensing technology, applied in the field of image processing, can solve problems such as limited application and limited Grouplet transformation, achieve wide application prospects, and eliminate redundancy and waste of resources.

Inactive Publication Date: 2016-08-24
NANCHANG HANGKONG UNIVERSITY
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Problems solved by technology

Domestic research on Grouplet transformation is still very limited, most of the exi

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  • Image processing method based on group-wave transformation compressed sensing
  • Image processing method based on group-wave transformation compressed sensing
  • Image processing method based on group-wave transformation compressed sensing

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[0045] The present invention will be further described below in conjunction with the accompanying drawings, implementation principles, simulation examples, etc., referring to the accompanying drawings and descriptions.

[0046] 1. The basic principle and algorithm of image compression sensing based on group wave transform:

[0047] 1.1 The principle of group wave transformation:

[0048] Such as figure 2As shown, the wavelet transform decomposition includes the calculation of the correlation domain layer and the coefficient layer, where the coefficient layer includes the average layer composed of low-frequency coefficients and the detail layer composed of high-frequency coefficients. The search of the correlation domain in group wave transform has a great influence on the performance of the transform. Group wave transformation uses block matching algorithm to find the correlation domain, this method can accurately reflect the change of each pixel, but it can't adapt to sele...

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Abstract

The invention discloses an image processing method based on group-wave transformation compressed sensing. The method specifically comprises the steps that orthogonal group-wave transformation is carried out to an image at first, so that sparsity coefficients in each directional scale are obtained; then high-frequency coefficients of each scale are compressed, measured and encoded; and finally, orthogonal group-wave inverse transformation is carried out to stored low-frequency coefficients and recovered high-frequency coefficients, so that a recovered image is obtained. The method has the advantages that sparse representation of group-wave transformation is fully integrated into the compressed sensing; image geometrical characteristics are utilized to the hilt; redundancy and resource waste caused by traditional Nyquist sampling theories are eliminated; texture information such as directions and scales of images can be further excavated; and high-definition images can be recovered when only a few of sampling points can be provided. In comparison with the existing method of wavelet transformation compressed sensing, the method disclosed by the invention has obvious advantages and has very broad application prospect in image processing.

Description

technical field [0001] The invention relates to an image processing method, which is an image processing method based on Grouplet transform compression sensing. Background technique [0002] Compressed Sensing Theory [1-3] Mainly for sparse signals or compressible signals, the data is properly compressed while acquiring the signal. Its sampling frequency is much lower than the Nyquist frequency. At the same time, it can reduce sampling data, eliminate a lot of redundancy, and save storage space. Contains enough information to reconstruct the original signal. At the same time, compressed sensing combines traditional data acquisition and data compression into one, but does not require complex data encoding algorithms. When necessary, appropriate reconstruction algorithms can be used to recover enough data points from the data obtained by compressed sensing. The theory of compressive sensing uses the sparsity of signals and images under the orthogonal basis as the prior basis...

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Application Information

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IPC IPC(8): G06T9/00
CPCG06T9/00
Inventor 李志农侯娟闫静文
Owner NANCHANG HANGKONG UNIVERSITY
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