Title :
No reference image quality assessment
Author :
Mandgaonkar, V.S. ; Kulkarni, C.V.
Author_Institution :
Dept. of Electron. & Telecomm. MITCOE, Univ. of Pune, Pune, India
Abstract :
The implementation of algorithm for no reference image quality assessment is presented. Aim of the project is to implement an image quality assessment algorithm which will assess the quality of the test image without any reference and predict the quality score for the test image. No Reference (blind) quality assessment problem is important as well as technically difficult. The algorithm used is a Natural Scene Statistics (NSS) model of discrete cosine transform (DCT) coefficients. NSS model based features are extracted. A regression model of SVM is used to predict image quality scores from certain extracted features. The features are based on an NSS model of the image DCT coefficients. The estimated parameters of the model are utilized to extract features that are indicative of perceptual quality.
Keywords :
discrete cosine transforms; feature extraction; natural scenes; regression analysis; support vector machines; NSS model; SVM; discrete cosine transform; feature extraction; image DCT coefficients; image quality scores prediction; natural scene statistics; no reference image quality assessment; perceptual quality; regression model; Computational modeling; Discrete cosine transforms; Feature extraction; Image quality; Prediction algorithms; Predictive models; Support vector machines; Discrete Cosine Transform; Natural Scene Statistics; No reference Image quality assessment;
Conference_Titel :
India Conference (INDICON), 2014 Annual IEEE
Conference_Location :
Pune
Print_ISBN :
978-1-4799-5362-2
DOI :
10.1109/INDICON.2014.7030678
