Efficient estimation of ideal-observer performance in classification tasks involving high-dimensional complex backgrounds.

@article{Park2009EfficientEO,
  title={Efficient estimation of ideal-observer performance in classification tasks involving high-dimensional complex backgrounds.},
  author={Subok Park and Eric Clarkson},
  journal={Journal of the Optical Society of America. A, Optics, image science, and vision},
  year={2009},
  volume={26 11},
  pages={B59-71}
}
The Bayesian ideal observer is optimal among all observers and sets an absolute upper bound for the performance of any observer in classification tasks [Van Trees, Detection, Estimation, and Modulation Theory, Part I (Academic, 1968).]. Therefore, the ideal observer should be used for objective image quality assessment whenever possible. However, computation of ideal-observer performance is difficult in practice because this observer requires the full description of unknown, statistical… CONTINUE READING

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