Title:
SINGLE-FRAME IMAGE SUPER-RESOLUTION RECONSTRUCTION METHOD
Document Type and Number:
WIPO Patent Application WO/2021/022929
Kind Code:
A1
Abstract:
The present invention discloses a single-frame image super-resolution reconstruction method, the method includes: establishing a consistent correspondence between low-resolution images and high-resolution images, according to the obtained 0 order gradient, 1 order gradient and 2 order gradient, establishing the observation models of structure, edge and texture respectively, further determining the multiple differential consistency constraint model; constructing a training set corresponding to the structure, edge, and texture levels between high-resolution images and low-resolution images; inputting the training set to the training model for training to obtain the priori constraint between high-resolution images and low-resolution images; using the semi-quadratic iterative method to establish a super-resolution reconstruction model according to the multiple differential consistency constraint model and the priori constraint, and performing solution, to obtain high-resolution reconstructed images. The present invention constructs a multiple differential consistency constraint model based on multiple gradients, and uses the semi-quadratic iterative algorithm to effectively integrate internal and external information, improving the accuracy of super-resolution image reconstruction.
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Inventors:
ZHAO SHENGRONG (CN)
LIANG HU (CN)
DONG XIANGJUN (CN)
LIANG HU (CN)
DONG XIANGJUN (CN)
Application Number:
PCT/CN2020/098001
Publication Date:
February 11, 2021
Filing Date:
June 24, 2020
Export Citation:
Assignee:
UNIV QILU TECHNOLOGY (CN)
International Classes:
G06T5/00
Foreign References:
| CN110443768A | 2019-11-12 | |||
| CN109559278A | 2019-04-02 | |||
| CN109214989A | 2019-01-15 | |||
| CN108550115A | 2018-09-18 |
Other References:
ZHAO SHENGRONG: "Research on Variational Bayesian Image Super Resolution Algorithms Based on Adaptive Prior Models", CHINESE DOCTORAL DISSERTATIONS FULL-TEXT DATABASE, 1 May 2016 (2016-05-01), pages 1 - 167, XP055777596
SUN XU, XIAO-GUANG LI, JIA-FENG LI, LI ZHUO: "Review on Deep Learning Based Image Super-resolution Restoration Algorithms", ACTA AUTOMATICA SINICA, vol. 43, no. 5, 15 May 2017 (2017-05-15), pages 697 - 709, XP055777613, ISSN: 0254-4156, DOI: 10.16383/j.aas.2017.c160629
CHAO DONG; LOY CHEN CHANGE; HE KAIMING; TANG XIAOOU: "Image Super-Resolution Using Deep Convolutional Networks", IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 38, no. 2, 1 June 2015 (2015-06-01), pages 1 - 14, XP055572436, DOI: 10.1109/TPAMI.2015.2439281
LIANG YUDONG; WANG JINJUN; ZHOU SANPING; GONG YIHONG; ZHENG NANNING: "Incorporating image priors with deep convolutional neural networks for image super-resolution", NEUROCOMPUTING, vol. 194, 5 March 2016 (2016-03-05), pages 340 - 347, XP029523308, ISSN: 0925-2312, DOI: 10.1016/j.neucom.2016.02.046
SUN XU, XIAO-GUANG LI, JIA-FENG LI, LI ZHUO: "Review on Deep Learning Based Image Super-resolution Restoration Algorithms", ACTA AUTOMATICA SINICA, vol. 43, no. 5, 15 May 2017 (2017-05-15), pages 697 - 709, XP055777613, ISSN: 0254-4156, DOI: 10.16383/j.aas.2017.c160629
CHAO DONG; LOY CHEN CHANGE; HE KAIMING; TANG XIAOOU: "Image Super-Resolution Using Deep Convolutional Networks", IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 38, no. 2, 1 June 2015 (2015-06-01), pages 1 - 14, XP055572436, DOI: 10.1109/TPAMI.2015.2439281
LIANG YUDONG; WANG JINJUN; ZHOU SANPING; GONG YIHONG; ZHENG NANNING: "Incorporating image priors with deep convolutional neural networks for image super-resolution", NEUROCOMPUTING, vol. 194, 5 March 2016 (2016-03-05), pages 340 - 347, XP029523308, ISSN: 0925-2312, DOI: 10.1016/j.neucom.2016.02.046
Attorney, Agent or Firm:
FANG & ASSOCIATES (CN)
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