An artificial neural network for quality assessment in wireless imaging based on extraction of structural information

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 1, Issue , 2007, Pages

  Engelke, Ulrich ^a   Zepernick, Hans Jürgen ^a  

^a BLEKINGE INSTITUTE OF TECHNOLOGY   (Sweden)

Author keywords

Artificial neural network; Communication systems; Feature extraction; Image quality assessment

Indexed keywords

COMMUNICATION SYSTEMS; FEATURE EXTRACTION; IMAGE QUALITY;

INTENSITY MASKING; PERCEIVED QUALITY; QUALITY PREDICTION;

NEURAL NETWORKS;

EID: 34547501073     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2007.366141     Document Type: Conference Paper

References (9)

1. H. R. Wu and K. R. Rao (Ed.), Digital Videoimage Quality and Perceptual Coding, CRC Press, 2006.
2. Z. Wang et al, "Image quality assessment: From error visibility to structural similarity," IEEE Trans. on Image Processing, pp. 600-612, April 2004.
3. ITU-R, "Methodology for the subjective assessment of the quality of television pictures," Rec. BT.500-11, 2002.
4. T. M. Kusuma, A Perceptual-based Objective Quality Metric for Wireless Imaging, Ph.D. thesis, Curtin University of Technology, Perth, Australia, 2005.
5. Z. Wang, H. R. Sheikh, and A. C. Bovik, "No-reference perceptual quality assessment of JPEG compressed images," in Proc. of IEEE ICIP, Sept. 2002, pp. 477-480.
6. P. Marziliano et al, "A no-reference perceptual blur metric," in Proc. of IEEE ICIP, Sept. 2002, pp. 57-60.
7. S. Saha and R. Vemuri, "An analysis on the effect of image features on lossy coding performance," IEEE Signal Processing Letters, pp. 104-107, May 2000.
8. J.-R. Ohm, Multimedia Communication Technology, Springer, 2004.
9. C. M. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, 1995.