2D sub-optimum filters for sharpening interpolated satellite images by optimizing the structural similarity index measure

Author

Al Nuaimi, Saeed ; Al-Ahmad, Hussain ; Al-Mualla, M.

Author_Institution

Dept. of Electr. & Comput. Eng., Khalifa Univ., Sharjah, United Arab Emirates

fYear

2014

fDate

23-25 July 2014

Firstpage

668

Lastpage

672

Abstract

This paper deals with the design and analysis of 2D filters for improving the resolution of interpolated satellite images. The images are reduced first by a certain factor and then interpolated back to the original size. Linear phase 2D filters are designed to optimize the structural similarity index measure (SSIM). Then the satellite image is enlarged by the same factor and the 2D filter is used to sharpen the image. The performance of the new sub-optimum filters was assessed by using the peak signal to noise ratio (PSNR) and the SSIM on a variety of satellite images. It has been found that this method yields better results than optimizing the mean square error (MSE) or by using the sparse method.

Keywords

filtering theory; geophysical image processing; interpolation; mean square error methods; 2D sub-optimum filters; MSE; SSIM; interpolated satellite images; mean square error; peak signal to noise ratio; sparse method; structural similarity index measure; Adaptive filters; Algorithm design and analysis; Filtering algorithms; Image resolution; Interpolation; PSNR; Satellites; Interpolation; SSIM; Satellite Images; Sharpening Filter; Super-Resolution Algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Systems, Networks & Digital Signal Processing (CSNDSP), 2014 9th International Symposium on

Conference_Location

Manchester

Type

conf

DOI

10.1109/CSNDSP.2014.6923911

Filename

6923911