Image fusion and super-resolution achievement method based on variation and fractional order differential
What is Al technical title?
Al technical title is built by PatSnap Al team. It summarizes the technical point description of the patent document.
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
View PDF5 Cites 18 Cited by
Summary
Abstract
Description
Claims
Application Information
AI Technical Summary
This helps you quickly interpret patents by identifying the three key elements:
Problems solved by technology
Method used
Benefits of technology
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
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more
Image
Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
Click on the blue label to locate the original text in one second.
Reading with bidirectional positioning of images and text.
Smart Image
Examples
Experimental program
Comparison scheme
Effect test
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...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more
PUM
Login to view more
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
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more
Application Information
Patent Timeline
Application Date:The date an application was filed.
Publication Date:The date a patent or application was officially published.
First Publication Date:The earliest publication date of a patent with the same application number.
Issue Date:Publication date of the patent grant document.
PCT Entry Date:The Entry date of PCT National Phase.
Estimated Expiry Date:The statutory expiry date of a patent right according to the Patent Law, and it is the longest term of protection that the patent right can achieve without the termination of the patent right due to other reasons(Term extension factor has been taken into account ).
Invalid Date:Actual expiry date is based on effective date or publication date of legal transaction data of invalid patent.
Login to view more 
Login to view more