TY - GEN
T1 - Higher-order statistical models of visual images
AU - Simoncelli, Eero P.
N1 - Publisher Copyright:
© 1999 IEEE.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 1999
Y1 - 1999
N2 - This paper examines the empirical densities of natural photographic images, and shows that although they are highly non-Gaussian, they are quite regular and may be described using fairly simple parameterized density models. Two such models are described, and their ability to account for image content is demonstrated.
AB - This paper examines the empirical densities of natural photographic images, and shows that although they are highly non-Gaussian, they are quite regular and may be described using fairly simple parameterized density models. Two such models are described, and their ability to account for image content is demonstrated.
UR - http://www.scopus.com/inward/record.url?scp=33645974717&partnerID=8YFLogxK
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U2 - 10.1109/HOST.1999.778691
DO - 10.1109/HOST.1999.778691
M3 - Conference contribution
AN - SCOPUS:33645974717
T3 - Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999
SP - 54
EP - 57
BT - Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1999 IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999
Y2 - 14 June 1999 through 16 June 1999
ER -