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access icon free Image quality assessment scheme with topographic independent components analysis for sparse feature extraction

A no-reference objective metric for image quality assessment by integrating the topographic independent components analysis into feature extraction is presented. By taking the topographic relationship among the initially independent features into consideration, it extracts the features of more sparsity or independency which is essentially related to inherent quality. Evaluation results demonstrate that the proposed metric is able to predict the image quality accurately across various distortion types.

References

    1. 1)
    2. 2)
      • 7. Barlow, H.B.: ‘Possible principles underlying the transformation of sensory message’ in Rosenblith, W.A. (Ed.) ‘Sensory communication’ (MIT Press, Cambridge, NY, 1961), pp. 217234.
    3. 3)
    4. 4)
    5. 5)
    6. 6)
    7. 7)
      • 8. Sheikh, H.R., Wang, Z., Cormack, L., Bovik, A.C.: ‘LIVE image quality assessment database release 2http://live.ece.utexas.edu/research/quality, accessed September 2013.
    8. 8)
http://iet.metastore.ingenta.com/content/journals/10.1049/el.2013.4298
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content/journals/10.1049/el.2013.4298
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