Super-resolution image reconstruction method based on coupled partial differential equation model

A partial differential equation, low-resolution image technology, applied in the field of super-resolution image reconstruction based on coupled partial differential equation model, to achieve the effect of improving quality and improving visual effects
CN103473752AInactive Publication Date: 2013-12-25杨勇
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Patent Information

Authority / Receiving Office
CN Β· China
Current Assignee / Owner
杨勇
Publication Date
2013-12-25
Estimated Expiration
Not applicable Β· inactive patent

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Abstract

The invention discloses a super-resolution image reconstruction method based on a coupled partial differential equation model. According to the reconstruction method, two partial differential models are coupled through defining a weighting function by utilizing the respective advantages of TV (Total Variation) and FPDE (Fourth Partial Differential Equation) in image restoration, a large weight is adopted for a TV model at an image edge area so as to maintain the edge and texture details of images, the large weight is adopted for an FPDE model at an image flatness area so as to inhibit a staircase effect generated by the TV model, new models serve as normalization items to reconstruct a super-resolution images, and the visual effect of image reconstruction can be enhanced.
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Description

technical field

[0001] The invention relates to an image super-resolution reconstruction method, in particular to a super-resolution image reconstruction method based on a coupled partial differential equation model. Background technique

[0002] Due to the insufficient number of low-resolution images and the fuzzy operation of ill-conditioned conditions, the super-resolution image reconstruction method is ill-conditioned. Partial Differential Equations (PDE) have received widespread attention because they can overcome the ill-conditioned problem of super-resolution reconstruction, and have good noise reduction and edge preservation capabilities. According to the forward model of the degraded image sequence, this kind of method uses the prior knowledge of image and blur as the regularization to construct the regularized minimization functional, and solves the minimization functional to obtain high-resolution images.

[0003] The Total Variation method (Total Variation, TV) ...

Claims

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