Single-Frame Image Super-Resolution based on Singular Square Matrix Operator

被引：0

作者：

Rashkevych, Yurii ^{[1
]}

Peleshko, Dmytro ^{[2
]}

Vynokurova, Olena ^{[3
]}

Izonin, Ivan ^{[4
]}

Lotoshynska, Natalia ^{[4
]}

机构：

[1] Lviv Polytech Natl Univ, Educ & Int Relat, Lvov, Ukraine

[2] Univ IT Step Acad, Sci Res, Lvov, Ukraine

[3] Kharkiv Natl Univ Radio Elect, Control Syst Res Lab, Kharkov, Ukraine

[4] Lviv Polytech Natl Univ, Dept Publishing Informat Technol, Lvov, Ukraine

来源：

2017 IEEE FIRST UKRAINE CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (UKRCON) | 2017年

关键词：

single-frame image super-resolution; similarity measures; singular square matrix operator; PSNR metrics;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In the paper the method of single-frame image super-resolution based on the singular decomposition of matrix operator of the convergence square matrix operator is proposed. The characteristic vectors-features are obtained by using the Moore-Penrose pseudoinverse of matrix operator, which are used for enlarged image synthesis. The series of computational experiments based on images with fluctuation of intensity function are performed. The comparison results with others methods have confirmed the effectiveness of developed approach. The main advantages of proposed method for different enlargement coefficients are considered.

引用

页码：944 / 948

页数：5

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