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Image fusion and super-resolution achievement method based on variation and fractional order differential

A fractional differential and super-resolution technology, applied in the fields of image processing and information fusion, which can solve the problems of high spatial resolution and single function of the image to be fused.

Active Publication Date: 2014-06-11
云南联合视觉科技有限公司
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  • Application Information

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Problems solved by technology

[0005] The present invention provides an image fusion and super-resolution implementation method based on variation and fractional differentiation, which is used to solve the problem that the traditional image fusion method has a single function and has high requirements for the spatial resolution of the image to be fused

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  • Image fusion and super-resolution achievement method based on variation and fractional order differential
  • Image fusion and super-resolution achievement method based on variation and fractional order differential
  • Image fusion and super-resolution achievement method based on variation and fractional order differential

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Embodiment 1

[0042] Embodiment 1: as Figure 1-19 As shown, an image fusion and super-resolution implementation method based on variation and fractional differentiation, the steps of the method are as follows:

[0043] A. Combine multiple sources to be integrated l low resolution image as a multi-channel image , while introducing weighted multi-channel images ;in, for the first i images f i ( x , y ) weight coefficient;

[0044] B. Using the multi-channel image with weights in step A f ( x , y ) structure tensor eigenvalues ​​and eigenvectors to describe the change of its own information, and thus obtain a weighted multi-channel image f ( x , y ) gradient information V ( x , y );

[0045] C. In terms of super-resolution implementation, assume an ideal super-resolution fusion image I is known, through the downsampling operator matrix H Act on this image to obtain a low-resolution fused image HI ;

[0046] D. According to the gradient information obtained in step B...

Embodiment 2

[0071] Embodiment 2: as Figure 1-19 As shown, an image fusion and super-resolution implementation method based on variation and fractional differentiation, the steps of the method are as follows:

[0072] A. Combine multiple sources to be integrated l low resolution image as a multi-channel image , while introducing weighted multi-channel images ;in, for the first i images weight coefficient;

[0073] B. Using the multi-channel image with weights in step A f ( x , y ) structure tensor eigenvalues ​​and eigenvectors to describe the change of its own information, and thus obtain a weighted multi-channel image f ( x , y ) gradient information V ( x , y );

[0074] C. In terms of super-resolution implementation, assume an ideal super-resolution fusion image I is known, through the downsampling operator matrix H Act on this image to obtain a low-resolution fused image HI ; this process can be expressed as HI = P · I ·Q :

[0075] in,

[0076] ,

[0...

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Abstract

The invention relates to an image fusion and super-resolution achievement method based on variation and fractional order differential, and belongs to the field of image processing and information fusion. On the basis of image fusion and super-resolution achievement, a low-resolution source image to be fused is regarded as a multi-channel image, unit value representation of gradient characteristics of the multi-channel image is obtained through construction of structure tensor of the low-resolution source image, and an image fusion and super-resolution achievement model is established according to the same or similar gradient characteristics between the low-resolution fusion image and the multi-channel image; in the model, the fractional order differential and fractional order total-variation minimization achievement method is introduced to achieve noise suppression, image edge information is enhanced through diffusion of two-way filtering wave diffusion, and generation of false information is suppressed. The method overcomes the defect that with a traditional method, fusion and super-resolution achievement can not be performed at the same time and has good application prospects in the fields of target imaging, safety monitoring and the like.

Description

technical field [0001] The invention relates to an image fusion and super-resolution realization method based on variation and fractional differentiation, which belongs to the field of image processing and information fusion. Background technique [0002] Multi-source image fusion is to integrate multiple image information about a specific scene acquired by different types of sensors (or the same type of sensor at different times or in different ways) to generate a new interpretation of the scene, so that A clearer, more complete, more reliable description of the scene or goal. The images obtained through synthesis can effectively overcome the differences and limitations of single sensor image data in terms of geometry, spectrum, time, and spatial resolution, which is very beneficial to the identification, understanding, and positioning of events or physical phenomena. At present, this technology is widely used in computer vision, medical imaging and diagnosis, remote sensi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/50
Inventor 李华锋余正涛毛存礼郭剑毅李小松刘志远
Owner 云南联合视觉科技有限公司
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