Paper
24 January 2012 A no-reference image quality metric for blur and ringing effect based on a neural weighting scheme
Aladine Chetouani, Azeddine Beghdadi
Author Affiliations +
Proceedings Volume 8293, Image Quality and System Performance IX; 82930D (2012) https://doi.org/10.1117/12.908021
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States
Abstract
No Reference Image Quality Metrics proposed in the literature are generally developed for specific degradations, limiting thus their application. To overcome this limitation, we propose in this study a NR-IQM for ringing and blur distortions based on a neural weighting scheme. For a given image, we first estimate the level of blur and ringing degradations contained in an image using an Artificial Neural Networks (ANN) model. Then, the final index quality is given by combining blur and ringing measures by using the estimated weights through the learning process. The obtained results are promising.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Aladine Chetouani and Azeddine Beghdadi "A no-reference image quality metric for blur and ringing effect based on a neural weighting scheme", Proc. SPIE 8293, Image Quality and System Performance IX, 82930D (24 January 2012); https://doi.org/10.1117/12.908021
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Cited by 1 scholarly publication.
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KEYWORDS
Image quality

Artificial neural networks

Databases

Image compression

Visualization

Image processing

JPEG2000

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