Title :
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
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;
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2008.4633899
