Multiple Channel Model For The Prediction Of Subjective Image Quality
by ,
Abstract:
A model for the perception of distortions in pictures is suggested. It consists of two main parts: an adaptive input stage realized as a ROG (Ratio of Gaussian) pyramid also suited for applications in image coding and computer vision, and a further decomposition by orientation selective filters including a saturating nonlinearity acting at each point of the filter outputs. The output values for each point of each filter are regarded as feature vector of the internal representation of the input picture. The difference between the internal representations of original and distorted picture is evaluated as norm of the difference vector. Due to local nonlinearities this operation explains periodic and aperiodic masking effects.
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PDF URL: http://dx.doi.org/10.1117/12.952719
Reference:
Multiple Channel Model For The Prediction Of Subjective Image Quality (C. Zetzsche, G. Hauske), In Human Vision, Visual Processing, and Digital Display (Bernice E. Rogowitz, ed.), SPIE-Intl Soc Optical Eng, volume 1077, 1989.
Bibtex Entry:
@InProceedings{Zetzsche1989b,
  author    = {C. Zetzsche and G. Hauske},
  title     = {Multiple Channel Model For The Prediction Of Subjective Image Quality},
  booktitle = {Human Vision, Visual Processing, and Digital Display},
  year      = {1989},
  editor    = {Bernice E. Rogowitz},
  volume    = {1077},
  pages     = {209-216},
  month     = {aug},
  publisher = {{SPIE}-Intl Soc Optical Eng},
  abstract  = {A model for the perception of distortions in pictures is suggested. It consists of two main parts: an adaptive input stage realized as a ROG (Ratio of Gaussian) pyramid also suited for applications in image coding and computer vision, and a further decomposition by orientation selective filters including a saturating nonlinearity acting at each point of the filter outputs. The output values for each point of each filter are regarded as feature vector of the internal representation of the input picture. The difference between the internal representations of original and distorted picture is evaluated as norm of the difference vector. Due to local nonlinearities this operation explains periodic and aperiodic masking effects.},
  doi       = {10.1117/12.952719},
  url       = {10.1117/12.952719">http://dx.doi.org/10.1117/12.952719},
}