Searched for: in-biosketch:yes
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Biases in white noise analysis due to non-Poisson spike generation
Pillow, JW; Simoncelli, EP
ISI:000183514300018
ISSN: 0925-2312
CID: 367362
Vision and the statistics of the visual environment
Simoncelli, Eero P
It is widely believed that visual systems are optimized for the visual properties of the environment inhabited by the organism. A specific instance of this principle is known as the Efficient Coding Hypothesis, which holds that the purpose of early visual processing is to produce an efficient representation of the incoming visual signal. The theory provides a quantitative link between the statistical properties of the world and the structure of the visual system. As such, specific instances of this theory have been tested experimentally, and have been used to motivate and constrain models for early visual processing
PMID: 12744966
ISSN: 0959-4388
CID: 143586
Seeing patterns in the noise
Simoncelli EP
How do observers detect the presence of objects or features in visual images? Stochastic stimuli (for example, white noise) have become popular choices for providing a linear characterization of early sensory mechanisms. A recent paper by Neri and Heeger takes this type of methodology a step further, and succeeds in isolating and characterizing non-linear mechanisms responsible for the detection and identification of a specific visual target
PMID: 12584015
ISSN: 1879-307x
CID: 143584
Directly invertible nonlinear divisive normalization pyramid for image representation [Meeting Abstract]
Valerio, R; Simoncelli, EP; Navarro, R
ISI:000187785500041
ISSN: 0302-9743
CID: 367382
On advances in statistical modeling of natural images [Meeting Abstract]
Srivastava, A; Lee, AB; Simoncelli, EP; Zhu, SC
ISI:000180135300003
ISSN: 0924-9907
CID: 367372
Image denoising using scale mixtures of Gaussians in the wavelet domain
Portilla, Javier; Strela, Vasily; Wainwright, Martin J; Simoncelli, Eero P
We describe a method for removing noise from digital images, based on a statistical model of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian vector and a hidden positive scalar multiplier. The latter modulates the local variance of the coefficients in the neighborhood, and is thus able to account for the empirically observed correlation between the coefficient amplitudes. Under this model, the Bayesian least squares estimate of each coefficient reduces to a weighted average of the local linear estimates over all possible values of the hidden multiplier variable. We demonstrate through simulations with images contaminated by additive white Gaussian noise that the performance of this method substantially surpasses that of previously published methods, both visually and in terms of mean squared error
PMID: 18244692
ISSN: 1057-7149
CID: 143612
Multiscale structural similarity for image quality assessment
Chapter by: Wang, Z.; Simoncelli, Eero P; Bovik, A.C.
in: Conference Record of the 37th Asilomar Conference on Signals, Systems and Computers by
Piscataway, N.J. : IEEE, 2003
pp. 1398-1402
ISBN: 0-7803-8104-1
CID: 371752
Image restoration using Gaussian scale mixtures in the wavelet domain
Chapter by: Portilla, J.; Simoncelli, Eero P
in: Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429) by
Piscataway, N.J. : IEEE, 20003
pp. 965-968
ISBN: 0-7803-7750-8
CID: 371762
Maximum likelihood estimation of a stochastic integrate - and - fire cascade spiking model [Meeting Abstract]
Paninski, L. M.; Pillow, J. W.; Simoncelli, Eero P
BIOSIS:PREV200400200571
ISSN: 1558-3635
CID: 371932
Characterization of nonlinear spatiotemporal properties of macaque retinal ganglion cells using spike - triggered covariance [Meeting Abstract]
Pillow, J. W.; Simoncelli, Eero P; Chichilnisky, E. J.
BIOSIS:PREV200400203886
ISSN: 1558-3635
CID: 371942