@article{d48500cb70d14e239f08edb4d1569761,
title = "Linear-Quadratic Noise-Smoothing Filters for Quantum-Limited Images",
abstract = "In this correspondence, we consider the use of nonlinear estimators for the noise smoothing of images obtained under quantum-limited imaging conditions. A Volterra expansion is investigated from which a set of linear-quadratic filters is derived using higher order statistics. The filters are applicable for single frame and multiple frames of a single scene imaged under low-light levels.",
author = "Chan, {Cheuk L.} and Katsaggelos, {Aggelos K.} and Sahakian, {A. V.}",
note = "Funding Information: Various approaches for postprocessing of images degraded by quantum noise have been proposed in the past. Because this type of noise is typically placed into the class of signal-dependent degradations, the majority of these techniques lie in the specification of a nonstationary model for the description of the noise [4], [5], resulting in a genre of nonstationary filters that operate independently at each pixel. This is intuitive with the notion of signal-dependent noise; however, these techniques also have a common feature in that they are linear. PTde it is well known that a nonlinear filter will generally Manuscript received August 18, 1993; revised October 28, 1994. This work was supported in part by a grant from Siemens. The associate editor coordinating the review of this paper and approving it for publication was Dr. Hsueh-Ming Hang.",
year = "1995",
month = sep,
doi = "10.1109/83.413179",
language = "English (US)",
volume = "4",
pages = "1328--1333",
journal = "IEEE Transactions on Image Processing",
issn = "1057-7149",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "9",
}