A Multicomponent Image Quality Assessment based on Singular Value Decomposition

Author

Boubas, Anas Y. ; Bettayeb, Maamar

Author_Institution

Comput. Sci. Dept., Univ. of Sharjah, Sharjah, United Arab Emirates

fYear

2007

fDate

24-27 Nov. 2007

Firstpage

141

Lastpage

144

Abstract

Most of the image quality measures rely on the amount of noise added to the image. Determination of both the noise amount and its type is crucial, as some applications may be sensitive to some noise types more than the others. We propose a new multicomponent quality measure that is based on singular value decomposition (SVD), and provide a way to identify some noise types using different components of the measure. The measure is compared to peak signal to noise ratio (PSNR), and is shown to distinguish between noise types the PSNR is not able to distinguish between. Standard images were used in the experiments.

Keywords

image processing; singular value decomposition; PSNR; SVD; image noise; multicomponent image quality assessment; peak signal to noise ratio; singular value decomposition; Area measurement; Biomedical measurements; Computer science; Image quality; Linear algebra; Matrix decomposition; Noise measurement; PSNR; Signal processing; Singular value decomposition; PSNR; image quality; local error measurement; objective measures; singular value decomposition; subjective evaluation;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communications, 2007. ICSPC 2007. IEEE International Conference on

Conference_Location

Dubai

Print_ISBN

978-1-4244-1235-8

Electronic_ISBN

978-1-4244-1236-5

Type

conf

DOI

10.1109/ICSPC.2007.4728275

Filename

4728275