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
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;
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
DOI :
10.1109/CISP.2010.5646285