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Peter Blomgren

dblp:83/1261 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 1998
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 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 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing
image restoration		 0.011998
Color TV: total variation methods for restoration of vector-valued images · IEEE Trans. Image Process. 1998
Image and video processing › regularization
total variation regularization		 0.011998
Color TV: total variation methods for restoration of vector-valued images · IEEE Trans. Image Process. 1998
Image and video processing › image restoration › inverse problem › inverse problem regularization › image regularization
vectorial total variation		 0.011998
Color TV: total variation methods for restoration of vector-valued images · IEEE Trans. Image Process. 1998
Image and video processing › image restoration › image denoising
color image denoising		 0.011998
Color TV: total variation methods for restoration of vector-valued images · IEEE Trans. Image Process. 1998

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

total variation minimization · 0.0
YearPublicationVenuePosition
1998 Color TV: total variation methods for restoration of vector-valued images
abstract
We propose a new definition of the total variation (TV) norm for vector-valued functions that can be applied to restore color and other vector-valued images. The new TV norm has the desirable properties of 1) not penalizing discontinuities (edges) in the image, 2) being rotationally invariant in the image space, and 3) reducing to the usual TV norm in the scalar case. Some numerical experiments on denoising simple color images in red-green-blue (RGB) color space are presented.
Peter Blomgren, Tony F. Chan
 IEEE Trans. Image Process.1
1997 Total variation image restoration: numerical methods and extensions
abstract
We describe some numerical techniques for the total variation image restoration method, namely a primal-dual linearization for the Euler-Lagrange equations and some preconditioning issues. We also highlight extension of this technique to color images, blind deconvolution and the staircasing effect.
Peter Blomgren, Tony F. Chan, Pep Mulet, Chak-Kuen Wong
 ICIP (3)1