Refactoring method for optimizing super resolution of facial images

A technology for super-resolution reconstruction and facial image, which is applied in the field of optimized super-resolution reconstruction of facial images, which can solve the problems of insufficient image precision and degradation of face recognition performance, and achieve high-precision reconstruction and suppress glitches Effect

Inactive Publication Date: 2013-03-27
HUBEI WEIJIA TECH
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Problems solved by technology

[0003] However, the accuracy of the image reconstructed by the existing super-resolution reconstruction method is not enough, resulting in a serious decline in the performance of face recognition.

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  • Refactoring method for optimizing super resolution of facial images
  • Refactoring method for optimizing super resolution of facial images
  • Refactoring method for optimizing super resolution of facial images

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Embodiment Construction

[0048] The present invention will be further described below in conjunction with embodiment:

[0049] Such as figure 1 As shown, the detailed calculation steps of an optimized face image super-resolution reconstruction method in the embodiment of the present invention are described as follows:

[0050] A method for optimizing face image super-resolution reconstruction, comprising the following steps:

[0051] Step 1), first take the input low-resolution face image I and K low-resolution reference face images I with the closest Euclidean distance to the input low-resolution face image I k (x), low-resolution reference face image I k (x) The image translated by p units by the affine translation operator is I k (x+p); Preferably, K=6 is used to ensure both reconstruction accuracy and calculation speed.

[0052] Step 2), input low-resolution face image I and K low-resolution reference face images I with the closest Euclidean distance to the input low-resolution face image I in...

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Abstract

The invention belongs to the field of refactoring of the super resolution of facial images and particularly provides a refactoring method for optimizing the super resolution of the facial images. The method includes step one, inputting a low-resolution facial image and K low-resolution reference facial image; step two, calculating a local embedding coefficient; step three, substituting a local embedding system into a refactoring model to calculate a refactored image with a high resolution; and step four, taking the image solved in the last step as an input image. The method can improve the face recognition accuracy.

Description

technical field [0001] The invention belongs to the field of image super-resolution reconstruction, in particular to a super-resolution reconstruction method for optimizing human face images. Background technique [0002] Patent No. 201210164069.9 discloses a super-resolution face recognition method based on multi-manifold discriminant analysis. In the training phase, the method obtains a multi-manifold image composed of low-resolution and high-resolution face images through multi-manifold discriminant analysis. A mapping matrix from the space to the multimanifold space of high-resolution face images. Construct the intra-class similarity graph and inter-class similarity graph in the multi-manifold space of the original high-resolution face image, use these two neighbor graphs to construct the discriminant constraint item, and optimize the cost function composed of the reconstruction constraint item and the discriminant constraint item , to get the mapping matrix. In the re...

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Application Information

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IPC IPC(8): G06K9/00
Inventor 不公告发明人
Owner HUBEI WEIJIA TECH
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