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Image Fusion Method Based on Distributed Compressive Sensing

A compressed sensing and image fusion technology, applied in the field of image processing, can solve the problem of high computational complexity, and achieve the effect of increasing sparsity, reducing the amount of fusion computation, and reducing computational complexity

Active Publication Date: 2017-07-04
XIANGTAN UNIV
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Problems solved by technology

[0007] In terms of image fusion, most of the current image fusion methods are based on wavelet transform. The original image is fused by using different fusion rules for the low-frequency coefficients and high-frequency coefficients after wavelet transform. These methods generally calculate high complexity

Method used

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  • Image Fusion Method Based on Distributed Compressive Sensing

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Embodiment approach

[0023] combine figure 1 The specific implementation is as follows:

[0024] Step 1. Input the original images A and B, and perform block clustering processing to obtain a set of matrix sub-blocks and Specific steps are as follows:

[0025] 1) Set X in area A and x B Select matrix sub-blocks in order and without aggregation and in and That is, the set of regions X A and x B There is only one matrix sub-block in each, which is the original image A and B, e is a positive integer, and the corresponding matrix sub-block is calculated and The ratio Γ of 0 elements to the total elements in the difference Δ;

[0026] 2) If Γ≤P, ​​P is the segmentation threshold, then the and Equally divided into 4 matrix sub-blocks to obtain a set of divided regions and update region set X A and x B ,Right now and l is a positive integer, enter 3);

[0027] If Γ>P, judge the area set X A and x B Whether all the elements in have been traversed, if so, stop spl...

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Abstract

The invention provides a distributed compressed sensing based image fusion method. The method includes: firstly inputting original images A and B and subjecting the original images A and B to blocking-clustering; then subjecting corresponding matrix sub-blocks to joint sparse transformation; subjecting a public sparse coefficient and a corresponding special sparse coefficient acquired after transformation to measurement matrix to acquire a public measurement value and a special measurement value, and then respectively subjecting the public measurement value and the corresponding special measurement value to fusion to acquire a fusion measurement value; reconstructing a fusion sparse coefficient of the fusion measurement value by applying a reconstructing algorithm; restoring the fusion sparse coefficient to fusion sub-images by adopting inverse transformation; finally subjecting the fusion sub-images to splicing to form a fusion image. The images are fused by adopting the distributed compressed sensing principle, calculation burden is lowered, and meanwhile quality of the fusion image is guaranteed.

Description

technical field [0001] The invention relates to an image fusion method based on distributed compressed sensing, which belongs to the field of image processing. Background technique [0002] Compressed sensing theory proposes a new data sampling method, which can sample signals at a rate much lower than the Nyquist sampling rate. Compressed sensing theory believes that as long as the signal is sparse or sparse in the transform domain, a high-dimensional signal can be projected onto a low-dimensional space with a measurement matrix unrelated to the sparse basis. These small projections include Sufficient information about the reconstructed signal, so that high-dimensional signals can be reconstructed with high probability using these projections by solving the optimal solution problem. [0003] With the introduction of compressed sensing theory, many branches emerged, and distributed compressed sensing is one of them. The theory of distributed compressed sensing fully explor...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/50G06T3/40
Inventor 罗光明汤成军裴廷睿李哲涛关屋大雄曹斌崔荣埈
Owner XIANGTAN UNIV
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