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Face super-resolution image processing method based on double-manifold alignment

A processing method and image-dividing technology, which is applied in the field of image processing, can solve problems such as unformed, and achieve the effect of improving the effect

Inactive Publication Date: 2009-12-23
FUDAN UNIV
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Problems solved by technology

[0002] At present, there are many difficulties in the research of face super-resolution, and no practical method and theoretical framework have been formed at this stage. The main difficulty lies in how to use a set of training images to construct the corresponding knowledge base, and reconstruct low-level images based on the knowledge base. High resolution solution of resolution test image

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  • Face super-resolution image processing method based on double-manifold alignment
  • Face super-resolution image processing method based on double-manifold alignment
  • Face super-resolution image processing method based on double-manifold alignment

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Embodiment Construction

[0022] Please refer to the accompanying drawings for a further description of the present invention.

[0023] First of all, the various details involved in this invention are described:

[0024] 1. Analysis of Procrustes

[0025] For two manifold data matrices X and Y, the goal of Procrustes alignment is to obtain the parameter k and the orthogonal transformation matrix Q, so that ||X-kYQ|| F minimum. Where||·|| F Represents the Frobenius norm, which is defined as: | | A | | F = trace ( A T A ) = Σ ij a ij 2 .

[0026] pair matrix Y T × X does singular value decomposition (Singular Value Decomposition, SVD) to get Y T X = USV T , let Q=UV T ,...

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Abstract

The invention provides a face super-resolution image processing method based on double-manifold alignment. Two heterogeneous manifolds of training-integrated high-resolution images and low-resolution images are subjected to double-manifold alignment in the space between a global face and a residual face, and then super-resolution algorithm is carried out. The invention has the advantage that the two heterogeneous manifolds of high-resolution images and low-resolution images are aligned by using Procrustes analysis, thereby improving the super-resolution effect of the images by the learning algorithm.

Description

technical field [0001] The invention relates to an image processing method, in particular to a face super-resolution image processing method based on dual-manifold alignment. Background technique [0002] At present, there are many difficulties in the research of face super-resolution, and no practical method and theoretical framework have been formed at this stage. The main difficulty lies in how to use a set of training images to construct the corresponding knowledge base, and reconstruct low-level images based on the knowledge base. A high-resolution solution of the resolution test image. [0003] The goal of image super-resolution is to reconstruct a high-resolution image from one or more low-resolution images. At present, the main super-resolution algorithms are interpolation-based, reconstruction-based and learning-based. [0004] Face super-resolution is a special field in image super-resolution. The main reason is that faces have some similar topological structures...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
Inventor 张军平李想
Owner FUDAN UNIV
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