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Multi-focus image fusion method based on compressed sensing and energy rule

A multi-focus image, compressed sensing technology, applied in the field of multi-focus image fusion, to achieve the effect of improving the fusion effect and improving the effect

Inactive Publication Date: 2014-02-19
XIDIAN UNIV
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  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0007] The technical key to realize the object of the present invention is to design a new fusion rule based on energy, and introduce data similarity to solve the problem of high similarity of multi-focus image blocks and improve the fusion effect

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  • Multi-focus image fusion method based on compressed sensing and energy rule
  • Multi-focus image fusion method based on compressed sensing and energy rule
  • Multi-focus image fusion method based on compressed sensing and energy rule

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Embodiment Construction

[0030] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0031] Step 1, input two multi-focus images, and perform block preprocessing on the two multi-focus images.

[0032] Input two multi-focus images A and B, and divide them into blocks, get n pairs of N×N image blocks and pull each pair of image blocks into columns, which are respectively expressed as Ai and Bi, i=1, 2, . .., n, n is the logarithm of the image block, N is the window size of the image block, N>1, in the example of the present invention, the values ​​of N are 8, 16, 32, 64 respectively.

[0033] Step 2: Observing the image block using the observation matrix to obtain an observation vector.

[0034] The image compression sensing observation process is a linear process. In order to be able to reconstruct accurately, the observation matrix and the sparse transformation matrix must satisfy the finite isometric property. The observation matrix Φ used for the image...

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Abstract

The invention discloses a multi-focus image fusion method based on compressed sensing and an energy rule. The multi-focus image fusion method based on compressed sensing and the energy rule mainly solves the problems that the similarity of image blocks is high in the process of multi-focus image fusion under the condition of compressed sensing, and information cannot be easily extracted. The multi-focus image fusion method based on the compressed sensing and the energy rule comprises the steps of observing two multi-focus images through the Hadamard measurement matrix used for block scrambling to obtain observation vectors of the two input images, calculating the fusion weight through energy and the data similarity of the two observation vectors, calculating an observation vector of a fused image according to the fusion weight, and carrying out reconstruction on the observation vector through a gradient projection method on a CDF9 / 7 wavelet basis to obtain the fused image. Compared with a classic multi-focus image fusion method, the multi-focus image fusion method based on compressed sensing and the energy rule has the advantages that information of the two images can be included at the same time, the fusion weight can be adjusted by adjusting items according to the similarity of the image blocks, the problem that the similarity of the multi-focus image blocks is excessively high is solved, the fusion effect is improved, and the multi-focus image fusion method can be used for fusion of the multi-focus images.

Description

technical field [0001] The invention belongs to the technical field of image processing and relates to a multi-focus image fusion method, which can be used for subsequent image interpretation, target detection, and target recognition of multi-focus images. Background technique [0002] Image fusion refers to extracting different original images through certain fusion rules and synthesizing their complementary information to obtain images that describe the same target or scene more accurately, comprehensively and reliably, that is, fused images. The original image can come from the same sensor or different sensors, and the fused image can make full use of the complementary information provided by the original image to provide more reliable information for subsequent image processing such as image interpretation, target detection, and target recognition. Image fusion can be mainly divided into three categories: pixel-level image fusion, feature-level image fusion and decision-...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/50
Inventor 焦李成刘芳戴金洪马晶晶马文萍王爽侯彪侯小瑾刘坤
Owner XIDIAN UNIV
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