Optimal Sampling of Natural Images: A Design Principle for the Visual System
Abstract
We formulate the problem of optimizing the sampling of natural images using an array of linear filters. Optimization of information capacity is constrained by the noise levels of the individual channels and by a penalty for the construction of long-range interconnections in the array. At low signal-to-noise ratios the optimal filter characteristics correspond to bound states of a Schrodinger equation in which the signal spectrum plays the role of the potential. The resulting optimal filters are remarkably similar to those observed in the mammalian visual cortex and the retinal ganglion cells of lower vertebrates. The observed scale invariance of natural images plays an essential role in this construction.
Cite
Text
Bialek et al. "Optimal Sampling of Natural Images: A Design Principle for the Visual System." Neural Information Processing Systems, 1990.Markdown
[Bialek et al. "Optimal Sampling of Natural Images: A Design Principle for the Visual System." Neural Information Processing Systems, 1990.](https://mlanthology.org/neurips/1990/bialek1990neurips-optimal/)BibTeX
@inproceedings{bialek1990neurips-optimal,
title = {{Optimal Sampling of Natural Images: A Design Principle for the Visual System}},
author = {Bialek, William and Ruderman, Daniel L. and Zee, A.},
booktitle = {Neural Information Processing Systems},
year = {1990},
pages = {363-369},
url = {https://mlanthology.org/neurips/1990/bialek1990neurips-optimal/}
}