DocumentCode :
1889766
Title :
Quality Assessment of Gaussian Blurred Images Using Symmetric Geometric Moments
Author :
Wee, Chong-Yaw ; Paramesran, Raveendran ; Mukundan, R.
Author_Institution :
Univ. of Malaya, Kuala Lumpur
fYear :
2007
fDate :
10-14 Sept. 2007
Firstpage :
807
Lastpage :
812
Abstract :
A novel objective full-reference image quality assessment metric based on symmetric geometric moments (SGM) is proposed. SGM is used to represent the structural information in the reference and test images. The reference and test images are divided into (8 times 8) blocks and the SGM up to fourth order for each block is computed. SGM of the corresponding blocks of the reference and test images are used to form the correlation index or quality metric of each block. The correlation index of the test image is then obtained by taking the average of all blocks. The performance of the proposed metric is validated through subjective evaluation by comparing with objective methods (PSNR and MSSIM) on a database of 174 Gaussian blurred images. The proposed metric performs better than PSNR and MSSIM by providing larger correlation coefficients and smaller errors after nonlinear regression fitting.
Keywords :
Gaussian processes; computational geometry; correlation methods; image processing; Gaussian blurred image quality assessment; correlation index; symmetric geometric moment; Computer science; Humans; Image analysis; Image databases; Image quality; Layout; PSNR; Quality assessment; Software engineering; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Analysis and Processing, 2007. ICIAP 2007. 14th International Conference on
Conference_Location :
Modena
Print_ISBN :
978-0-7695-2877-9
Type :
conf
DOI :
10.1109/ICIAP.2007.4362875
Filename :
4362875
Link To Document :
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