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Stefan Held

dblp:28/8116 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2010
—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 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing › image enhancement
contrast enhancement
0.112010
Steerable Wavelet Frames Based on the Riesz Transform · IEEE Trans. Image Process. 2010
Image and video processing
image enhancement
0.112010
Steerable Wavelet Frames Based on the Riesz Transform · IEEE Trans. Image Process. 2010
Image and video processing
image transform
0.112010
Steerable Wavelet Frames Based on the Riesz Transform · IEEE Trans. Image Process. 2010
Image and video processing › wavelet transform
steerable wavelet frame
0.112010
Steerable Wavelet Frames Based on the Riesz Transform · IEEE Trans. Image Process. 2010

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

riesz transform · 0.1clifford frame · 0.1
YearPublicationVenuePosition
2010 Steerable Wavelet Frames Based on the Riesz Transform
abstract
We consider an extension of the 1-D concept of analytical wavelet to n-D which is by construction compatible with rotations. This extension, called a monogenic wavelet, yields a decomposition of the wavelet coefficients into amplitude, phase, and phase direction. The monogenic wavelet is based on the hypercomplex monogenic signal which is defined using Riesz transforms and perfectly isotropic wavelets frames. Employing the new concept of Clifford frames, we can show that the monogenic wavelet generates a wavelet frame. Furthermore, this approach yields wavelet frames that are steerable with respect to direction. Applications to descreening and contrast enhancement illustrate the versatility of this approach to image analysis and reconstruction.
Stefan Held, Martin Storath, Peter Massopust, Brigitte Forster-Heinlein
IEEE Trans. Image Process.1