24 January 2012 A no-reference image quality metric for blur and ringing effect based on a neural weighting scheme
Author Affiliations +
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, Aladine Chetouani, Azeddine Beghdadi, 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); doi: 10.1117/12.908021; https://doi.org/10.1117/12.908021
PROCEEDINGS
8 PAGES


SHARE
RELATED CONTENT

SPCA a no reference image quality assessment based on...
Proceedings of SPIE (February 04 2013)
An ICA-based approach for image quality assessment
Proceedings of SPIE (October 30 2009)
Blockiness in JPEG-coded images
Proceedings of SPIE (May 19 1999)

Back to Top