DocumentCode
1791372
Title
No-reference image quality assessment using dual-tree complex wavelet transform
Author
Xiaochun Zhong ; Chaofeng Li ; Wei Zhang ; Yiwen Ju
Author_Institution
Sch. of Internet of Things Eng., Jiangnan Univ., Wuxi, China
fYear
2014
fDate
14-16 Oct. 2014
Firstpage
596
Lastpage
601
Abstract
As discrete wavelet transform (DWT) is short in shift invariance and directionality, we proposed a no-reference image quality assessment (IQA) method based on dual-tree complex wavelet transform (DTCWT). In this method, an image is decomposed by DTCWT firstly. Then the energy value of each sub-band is calculated. Finally a support vector regressor (SVR) is adopted to predict image quality score. Experimental results show that our method is consistent well with human perception and has a low computational complexity.
Keywords
discrete wavelet transforms; image processing; regression analysis; support vector machines; DTCWT; IQA method; SVR; discrete wavelet transform; dual-tree complex wavelet transform; no-reference image quality assessment; support vector regressor; Databases; Discrete wavelet transforms; Feature extraction; Image quality; Measurement; dual-tree complex wavelet transform; energy; no-reference image quality assessment; support vector regressor;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing (CISP), 2014 7th International Congress on
Conference_Location
Dalian
Type
conf
DOI
10.1109/CISP.2014.7003849
Filename
7003849
Link To Document