The Principal Components of Natural Images Revisited

Heidemann G (2006)
IEEE Trans. on Pattern Analysis and Machine Intelligence 28(5): 822-826.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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DOI
Autor*in
Heidemann, Gunther
Einrichtung
Technische Fakultät > AG Neuroinformatik
Abstract / Bemerkung
This paper investigates the principal components (PCs) of natural gray and color images. A horizontal and vertical typology of PCs is found which leads to the identification of groups of basis functions for steerable bandpass filters. Using this system, the contribution of spatio-chromatic structure to the total variance can be quantified for selected spatial frequencies.
Erscheinungsjahr
2006
Zeitschriftentitel
IEEE Trans. on Pattern Analysis and Machine Intelligence
Band
28
Ausgabe
5
Seite(n)
822-826
ISSN
0162-8828
Page URI
https://pub.uni-bielefeld.de/record/2714142

Zitieren

Heidemann G. The Principal Components of Natural Images Revisited. IEEE Trans. on Pattern Analysis and Machine Intelligence. 2006;28(5):822-826.
Heidemann, G. (2006). The Principal Components of Natural Images Revisited. IEEE Trans. on Pattern Analysis and Machine Intelligence, 28(5), 822-826. doi:10.1109/TPAMI.2006.107
Heidemann, Gunther. 2006. “The Principal Components of Natural Images Revisited”. IEEE Trans. on Pattern Analysis and Machine Intelligence 28 (5): 822-826.
Heidemann, G. (2006). The Principal Components of Natural Images Revisited. IEEE Trans. on Pattern Analysis and Machine Intelligence 28, 822-826.
Heidemann, G., 2006. The Principal Components of Natural Images Revisited. IEEE Trans. on Pattern Analysis and Machine Intelligence, 28(5), p 822-826.
G. Heidemann, “The Principal Components of Natural Images Revisited”, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 28, 2006, pp. 822-826.
Heidemann, G.: The Principal Components of Natural Images Revisited. IEEE Trans. on Pattern Analysis and Machine Intelligence. 28, 822-826 (2006).
Heidemann, Gunther. “The Principal Components of Natural Images Revisited”. IEEE Trans. on Pattern Analysis and Machine Intelligence 28.5 (2006): 822-826.

3 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

On the preliminary psychophysics of fingerprint identification.
Vokey JR, Tangen JM, Cole SA., Q J Exp Psychol (Hove) 62(5), 2009
PMID: 19034812
Independence of color and luminance edges in natural scenes.
Hansen T, Gegenfurtner KR., Vis Neurosci 26(1), 2009
PMID: 19152717
Interpreting principal component analyses of spatial population genetic variation.
Novembre J, Stephens M., Nat Genet 40(5), 2008
PMID: 18425127

25 References

Daten bereitgestellt von Europe PubMed Central.

Possible Principles Underlying the Transformations of Sensory Messages
barlow, Sensory Comm (), 1961

AUTHOR UNKNOWN, 0
Amplitude spectra of natural images.
Tolhurst DJ, Tadmor Y, Chao T., Ophthalmic Physiol Opt 12(2), 1992
PMID: 1408179
Spatial frequency selectivity of cells in macaque visual cortex.
De Valois RL, Albrecht DG, Thorell LG., Vision Res. 22(5), 1982
PMID: 7112954
Color-opponent receptive fields derived from independent component analysis of natural images.
Tailor DR, Finkel LH, Buchsbaum G., Vision Res. 40(19), 2000
PMID: 10958917

AUTHOR UNKNOWN, 0

AUTHOR UNKNOWN, 0
The "independent components" of natural scenes are edge filters.
Bell AJ, Sejnowski TJ., Vision Res. 37(23), 1997
PMID: 9425547

AUTHOR UNKNOWN, 0
Chromatic structure of natural scenes.
Wachtler T, Lee TW, Sejnowski TJ., J Opt Soc Am A Opt Image Sci Vis 18(1), 2001
PMID: 11152005
Eigenfaces for recognition.
Turk M, Pentland A., J Cogn Neurosci 3(1), 1991
PMID: 23964806
Receptive fields, binocular interaction and functional architecture in the cat's visual cortex.
HUBEL DH, WIESEL TN., J. Physiol. (Lond.) 160(), 1962
PMID: 14449617
An Evaluation of the Two-Dimensional Gabor Filter Model of Simple Receptive Fields in Cat Striate Cortex
jones, J Neurophysiology 58(), 1987
The spatial transformation of color in the primary visual cortex of the macaque monkey.
Johnson EN, Hawken MJ, Shapley R., Nat. Neurosci. 4(4), 2001
PMID: 11276232

AUTHOR UNKNOWN, 0
Emergence of simple-cell receptive field properties by learning a sparse code for natural images.
Olshausen BA, Field DJ., Nature 381(6583), 1996
PMID: 8637596
Computational models of visual neurons specialised in the detection of periodic and aperiodic oriented visual stimuli: bar and grating cells.
Petkov N, Kruizinga P., Biol Cybern 76(2), 1997
PMID: 9116079

marr, Vision A Computational Investigation into the Human Representation and Processing of Visual Information (), 1982

AUTHOR UNKNOWN, 0
A simplified neuron model as a principal component analyzer.
Oja E., J Math Biol 15(3), 1982
PMID: 7153672

AUTHOR UNKNOWN, Art Explosion Photo Gallery (), 2002
Color in the cortex revisited.
Gegenfurtner K., Nat. Neurosci. 4(4), 2001
PMID: 11276215
View Invariant Object Recognition Using Coloured Receptive Fields
hall, Machine Graphics and Vision (), 2000

AUTHOR UNKNOWN, 0

AUTHOR UNKNOWN, 0
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