NONCONVEX REGULARIZATION FOR SHAPE PRESERVATION
Abstract
The authors show that using a nonconvex penalty term to regularize image reconstruction can substantially improve the preservation of object shapes. The commonlyused totalvariation regularization, {integral}{del}u, penalizes the length of the object edges. They show that {integral}{del}u{sup p}, 0 < p < 1, only penalizes edges of dimension at least 2p, and thus finitelength edges not at all. We give numerical examples showing the resulting improvement in shape preservation.
 Authors:
 Los Alamos National Laboratory
 Publication Date:
 Research Org.:
 Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
 OSTI Identifier:
 1000753
 Report Number(s):
 LAUR070291
TRN: US201101%%537
 DOE Contract Number:
 AC5206NA25396
 Resource Type:
 Conference
 Resource Relation:
 Conference: IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING ; 200709 ; SAN ANTONIO
 Country of Publication:
 United States
 Language:
 English
 Subject:
 99; DIMENSIONS; IMAGE PROCESSING; PRESERVATION; SHAPE
Citation Formats
CHARTRAND, RICK. NONCONVEX REGULARIZATION FOR SHAPE PRESERVATION. United States: N. p., 2007.
Web.
CHARTRAND, RICK. NONCONVEX REGULARIZATION FOR SHAPE PRESERVATION. United States.
CHARTRAND, RICK. Tue .
"NONCONVEX REGULARIZATION FOR SHAPE PRESERVATION". United States.
doi:. https://www.osti.gov/servlets/purl/1000753.
@article{osti_1000753,
title = {NONCONVEX REGULARIZATION FOR SHAPE PRESERVATION},
author = {CHARTRAND, RICK},
abstractNote = {The authors show that using a nonconvex penalty term to regularize image reconstruction can substantially improve the preservation of object shapes. The commonlyused totalvariation regularization, {integral}{del}u, penalizes the length of the object edges. They show that {integral}{del}u{sup p}, 0 < p < 1, only penalizes edges of dimension at least 2p, and thus finitelength edges not at all. We give numerical examples showing the resulting improvement in shape preservation.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jan 16 00:00:00 EST 2007},
month = {Tue Jan 16 00:00:00 EST 2007}
}
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