Feature Selection for Neural-Network Based No-Reference Video Quality Assessment-Reference-Cited by-同舟云学术

Feature Selection for Neural-Network Based No-Reference Video Quality Assessment

Published:2009 Issue: Volume: Page:633-642
ISSN:0302-9743
Container-title:Artificial Neural Networks – ICANN 2009
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Author:

Ćulibrk Dubravko,Kukolj Dragan,Vasiljević Petar,Pokrić Maja,Zlokolica Vladimir

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-04277-5_64

Reference14 articles.

1. Wang, Z., Sheikh, H.R., Bovik, A.C.: No-reference perceptual quality assessment of jpeg compressed images, pp. 477–480 (2002)

2. Warwick, G., Thong, N.: Classification of Video Sequences in MPEG Domain. In: Signal Processing for Telecommunications and Multimedia, ch. 6, Springer, Heidelberg (2004)

3. Kirenko, I.: Reduction of coding artifacts using chrominance and luminance spatial analysis. In: International Conference on Consumer Electronics, ICCE 2006, Digest of Technical Papers, pp. 209–210 (2006)

4. Ferzli, R., Karam, L.: A no-reference objective image sharpness metric based on just-noticeable blur and probability summation. In: IEEE International Conference on Image Processing, 2007. ICIP 2007, vol. 3, III –445–III –448 (2007)

5. BT.500, I.R.: Methodology for the Subjective Assessment of the Quality of Television Pictures (2002)

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2. No-Reference Video Quality Assessment Based on Artifact Measurement and Statistical Analysis;IEEE Transactions on Circuits and Systems for Video Technology;2015-04

3. No-reference image and video quality assessment: a classification and review of recent approaches;EURASIP Journal on Image and Video Processing;2014-08-14