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Pyramid Face Image Super-resolution Reconstruction Method Based on Regression Model

A technology of super-resolution reconstruction and face image, applied in the field of super-resolution reconstruction of pyramid face image based on regression model, which can solve the problem of face image ghosting without considering image quality, influence, and face image degradation process.

Inactive Publication Date: 2021-03-05
HEBEI UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The method of the present invention overcomes the problems in the prior art that the difference between the high-resolution images in the training set does not consider the influence of the difference between the high-resolution images in the training set on the quality of the reconstructed image in the prior art, and the face image reconstruction process cannot truly reflect the face image Defects in the degradation process and the defects that cause the reconstructed face image to still have partial ghosting

Method used

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  • Pyramid Face Image Super-resolution Reconstruction Method Based on Regression Model
  • Pyramid Face Image Super-resolution Reconstruction Method Based on Regression Model
  • Pyramid Face Image Super-resolution Reconstruction Method Based on Regression Model

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Embodiment 1

[0105] In this embodiment, the regression model based pyramid face image super resolution reconstruction method is as follows:

[0106] A. Training concentrated low resolution human face image set and high resolution human face image set training process:

[0107] First step, expansion training concentration low resolution human face image set and high resolution human face Images:

[0108]According to the characteristics of the face image symmetry, the low-resolution face image set and the high-resolution human face image set in the training concentration are expanded by the left and right ways. The size of the image is constant, the number is doubled, and the expansion is obtained. Low resolution facial image set And expanded high resolution human face image set Where l represents the low resolution image, the size is a * B pixel, H represents a high resolution image, the size is (D * a) * (D * b) pixel, D is multiple, the value of D is 2, m represents an image quantity;

[01...

Embodiment 2

[0177] In addition to R in the third step 1 The value is 10, the R of the fourth step 1 The value of 10 and R 1 The value of 10, the R 1The value of 10, the eighteenth step (18.3) is R 2 The value is 8, and the other as in Example 1.

Embodiment 3

[0179] In addition to R in the third step 1 The value of 12, the fourth step 1 The value of 12, the r 1 The value of 12, R 1 The value of the value is 12, the eighteenth step (18.3) 2 In addition to the value of 10, other embodiments 1.

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Abstract

The method for super-resolution reconstruction of pyramidal face images based on a regression model in the present invention involves image enhancement or restoration, using the feature of non-local similarity of images to search and reconstruct low-resolution face images in the test set in their corresponding feature images The similar blocks of the image block, get the position set of all similar blocks, and use the face image blocks of all the low-resolution images in the training set in the position set as the low-resolution training set corresponding to the low-resolution face image blocks in the test set , using the distance between the feature image blocks corresponding to the low-resolution face image blocks in the test set and the feature image blocks corresponding to the low-resolution face image blocks in the training set and the interpolated and enlarged low-resolution images in the test set The sum of the distances between the feature image block corresponding to the face image block and the feature image block corresponding to the high-resolution face image block in the training set constructs a constraint condition; it overcomes many defects in the process of face image reconstruction in the prior art.

Description

Technical field [0001] The technical solution of the present invention relates to an enhancement or recovery of an image, and is specifically a method of reconstructing a pyramid face image based on a regression model. Background technique [0002] During image acquisition, due to the influence of the imaging system, the acquired image and real scenes will tend to deviate. How to improve the spatial resolution of the image, improve image quality, have always been an important issue that the image acquisition technology is solved. With the development of science and technology, the performance of hardware equipment in imaging systems is getting better and better, but the method of improving image quality by lifting hardware systems requires high cost. Based on the hardware level has reached a certain height, improve the quality of the image by software is an economically effective method, and the super resolution, SR is based on this effective method. [0003] In general, the imag...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T3/40
CPCG06T3/4007G06T3/4076
Inventor 于明熊敏刘依郭迎春于洋师硕毕容甲
Owner HEBEI UNIV OF TECH
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