A no reference image quality assessment method for JPEG2000

Author

Zhou, Jingchao ; Xiao, Baihua ; Li, Qiudan

Author_Institution

Inst. of Autom., Chinese Acad. of Sci., Beijing

fYear

2008

fDate

1-8 June 2008

Firstpage

863

Lastpage

868

Abstract

This paper presents a novel no reference method to assess image quality. Firstly, the image is divided into many blocks. Textured blocks are selected and their amplitude fall-off curves are employed for quality prediction based on natural scene statistics. Secondly, projections of wavelet coefficients between adjacent scales with the same orientation are utilized to measure the positional similarity. At last, general regression neural network is adopted to conduct quality prediction according to features from above two aspects. The performance of our method is evaluated on a public data set and experimental results confirm its effectiveness.

Keywords

data compression; image coding; image texture; natural scenes; neural nets; regression analysis; wavelet transforms; JPEG2000; image quality prediction; image textured block; natural scene statistical feature; no reference image quality assessment; positional similarity measure; regression neural network; wavelet coefficient; Appraisal; Cognition; Discrete wavelet transforms; Distortion measurement; Feature extraction; Humans; Image coding; Image quality; Layout; Wavelet coefficients;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on

Conference_Location

Hong Kong

ISSN

1098-7576

Print_ISBN

978-1-4244-1820-6

Electronic_ISBN

1098-7576

Type

conf

DOI

10.1109/IJCNN.2008.4633899

Filename

4633899