Image Quality Assessment Based on Distortion-Aware Decision Fusion
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Publisher
Springer Berlin Heidelberg
Link
http://link.springer.com/content/pdf/10.1007/978-3-642-31919-8_82.pdf
Reference18 articles.
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3. Falk, T.H., Guo, Y., Chan, W.Y.: Improving Robustness of Image Quality Measurement with Degradation Classification and Machine Learning. In: 41st Asilomar Conference on Signals, Systems and Computers, Pacific Grove, pp. 503–507 (2007)
4. Liu, M., Yang, X.: Image Quality Assessment by Decision Fusion. IEICE Electronics Express 5(15), 537–542 (2008)
5. Hsu, C., Lin, C.: A Comparison of Methods for Multiclass Support Vector Machines. IEEE Trans. on Neural Networks 13(2), 415–425 (2002)
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3. F-MAD: a feature-based extension of the most apparent distortion algorithm for image quality assessment;SPIE Proceedings;2013-02-04
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