What's wrong with mean-squared error?
Digital images and human vision
DCT-domain blind measurement of blocking artifacts in DCT-coded images
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
A no-reference perceptual blur metric using histogram of gradient profile sharpness
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Image quality assessment based on the contourlet transform
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 1
Kurtosis-based no-reference quality assessment of JPEG2000 images
Image Communication
Visual quality assessment algorithms: what does the future hold?
Multimedia Tools and Applications
No-reference image quality assessment using structural activity
Signal Processing
Causes and subjective evaluation of blurriness in video frames
Image Communication
No-reference blur image quality measure based on multiplicative multiresolution decomposition
Journal of Visual Communication and Image Representation
International Journal of Communication Networks and Distributed Systems
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Perceptual image quality evaluation has become an important issue, due to increasing transmission of multimedia contents over the Internet and 3G mobile networks. Most of the no reference perceptual image quality evaluations traditionally attempted to quantify the predefined artifacts of the coded images. Under the assumption that human visual perception is very sensitive to edge information of an image and any kinds of artifacts create pixel distortion, we propose a new approach for designing a no reference image quality evaluation model for JPEG2000 images in this paper, which uses pixel distortions and edge information. Subjective experiment results on the images are used to train and test the model, which has achieved good quality prediction performance.