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Brian Hendee Smith

dblp:28/1326 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2000
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 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 · 100%

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

TopicWeightPapersLastEvidence papers
Image and video processing
image enhancement		 0.012000
Generalization of spatially variant apodization to noninteger Nyquist sampling rates · IEEE Trans. Image Process. 2000
Image and video processing › radar imaging › synthetic aperture radar imaging
sidelobe reduction		 0.012000
Generalization of spatially variant apodization to noninteger Nyquist sampling rates · IEEE Trans. Image Process. 2000
Image and video processing › radar imaging
synthetic aperture radar imaging		 0.012000
Generalization of spatially variant apodization to noninteger Nyquist sampling rates · IEEE Trans. Image Process. 2000

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

finite impulse response filter · 0.0
YearPublicationVenuePosition
2000 Generalization of spatially variant apodization to noninteger Nyquist sampling rates
abstract
Spatially variant apodization (SVA) is reformulated for use on synthetic aperture radar imagery with an arbitrary sampling rate. The algorithm is implemented as a spatially varying three-point finite impulse response filter, and constraints on the filter parameters are developed from physically motivated concepts. By varying the parameters of the filter, the sidelobe energy is reduced with no effective loss of resolution. The procedure produces an output comparable to that of the integer Nyquist version of SVA, and effectively eliminates sidelobe artifacts with no loss of mainlobe resolution.
Brian Hendee Smith
 IEEE Trans. Image Process.1