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Carlos A. Berenstein

dblp:322/6809 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1990
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Image and video processing · 87% Computational photography and imaging · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing › image restoration
image deblurring
0.011990
Exact deconvolution for multiple convolution operators-an overview, plus performance characterizations for imaging sensors · Proc. IEEE 1990
Image and video processing
image restoration
0.011990
Exact deconvolution for multiple convolution operators-an overview, plus performance characterizations for imaging sensors · Proc. IEEE 1990
Computational photography and imaging
image sensor
0.011990
Exact deconvolution for multiple convolution operators-an overview, plus performance characterizations for imaging sensors · Proc. IEEE 1990

Methods — techniques the papers use, named apart from their topics

inverse filtering · 0.0distribution theory · 0.0
YearPublicationVenuePosition
1990 Exact deconvolution for multiple convolution operators-an overview, plus performance characterizations for imaging sensors
abstract
An updated review of the subject, including physically realizable examples along with explicit inverses and a computer simulation of the resulting large bandwidth, is given. A discussion of the ill-posedness of a single convolution operator clarifies the necessity of multiple operators. A precisely stated necessary and sufficient condition for inevitability is given. The performance of simultaneous convolution operators when there are sources of additive noise prior to the inverse is addressed. The main point is that for noise typical of electrooptical sensors, invertible multiple operators with their inverses will always outperform any set of single or multiple operators with the inverse omitted. A tutorial on the theory of distributions of compact support, which is used freely throughout the paper, is given in the appendix.
Carlos A. Berenstein, E. Vincent Patrick
Proc. IEEE1