DocumentCode
3247593
Title
A correlation method of image quality assessment based on SVM and GA
Author
Wang, Lei ; Ding, Wenrui ; Xiang, Jinwu ; Cui, Le
Author_Institution
Sch. of Electron. & Inf. Eng., Beihang Univ., Beijing, China
Volume
1
fYear
2010
fDate
16-18 Oct. 2010
Firstpage
6
Lastpage
10
Abstract
In this paper, we propose a correlation method to assess image quality based on support vector machine (SVM) and genetic algorithm (GA). Instead of the simple linear function to correlate objective indicators with subjective scores of images, we introduce SVM for the correlation function, make GA as the search algorithm, and finally get the image quality assessment model. The results of experiments show: It is effective to introduce SVM to make correlation between objective indicators and subjective scores for image quality assessment; the correlation between objective indicators and subjective scores is better by using SVM based on GA.
Keywords
correlation methods; genetic algorithms; image processing; support vector machines; correlation method; genetic algorithm; image quality assessment model; support vector machine; Artificial neural networks; Correlation; Gallium; Image quality; Kernel; Support vector machines; Training; correlation method; genetic algorithm; image quality assessment; support vector machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location
Yantai
Print_ISBN
978-1-4244-6513-2
Type
conf
DOI
10.1109/CISP.2010.5646285
Filename
5646285
Link To Document