Super-resolution via a patch-based sparse algorithm

Author

Dashti, Maryam ; Ghidary, Saeed Shiry ; Hosseinian, Tahmineh ; Pourfard, Mohammadrez ; Faez, Karim

Author_Institution

Comput. Eng. & Inf. Technol., Amirkabir Univ. of Technol., Tehran, Iran

fYear

2015

fDate

3-5 March 2015

Firstpage

279

Lastpage

283

Abstract

The Sparsity concept has been widely used in image processing applications. In this paper, an approach for super-resolution has been proposed which uses sparse transform. This approach has mixed the inpainting concept with zooming via a sparse representation. A dictionary is being trained from a low-resolution image and then a zoomed version of this low resolution image will use that dictionary in a few iterations to fill the undefined image pixels. Experimental results confirm the strength of this algorithm against the other interpolation algorithms.

Keywords

image resolution; image restoration; interpolation; transforms; image pixel; image processing application; inpainting concept with zooming; interpolation algorithm; low-resolution image; patch-based sparse algorithm; sparse representation; sparse transform; sparsity concept; super-resolution; Dictionaries; Image resolution; Interpolation; Matching pursuit algorithms; Signal processing algorithms; Signal resolution; Training; Image processing; Inpainting; Patch-based algorithm; sparse transforms super resolution;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence and Signal Processing (AISP), 2015 International Symposium on

Conference_Location

Mashhad

Print_ISBN

978-1-4799-8817-4

Type

conf

DOI

10.1109/AISP.2015.7123496

Filename

7123496