Demo Data from EDBT 2026 / reviewers in the wild / expert
Amandine Blanc
dblp:62/4269
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
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 · 50% Computational photography and imaging · 50% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing
image restoration |
0.1 | 1 | 2005 | Statistical behavior of joint least-square estimation in the phase diversity context · IEEE Trans. Image Process. 2005 |
Computational photography and imaging
wavefront sensing |
0.1 | 1 | 2005 | Statistical behavior of joint least-square estimation in the phase diversity context · IEEE Trans. Image Process. 2005 |
Mathematical optimization
least squares |
0.1 | 1 | 2005 | Statistical behavior of joint least-square estimation in the phase diversity context · IEEE Trans. Image Process. 2005 |
Methods — techniques the papers use, named apart from their topics
maximum likelihood estimation · 0.1asymptotic theory of toeplitz matrices · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | Statistical behavior of joint least-square estimation in the phase diversity contextabstractThe images recorded by optical telescopes are often degraded by aberrations that induce phase variations in the pupil plane. Several wavefront sensing techniques have been proposed to estimate aberrated phases. One of them is phase diversity, for which the joint least-square approach introduced by Gonsalves et al. is a reference method to estimate phase coefficients from the recorded images. In this paper, we rely on the asymptotic theory of Toeplitz matrices to show that Gonsalves' technique provides a consistent phase estimator as the size of the images grows. No comparable result is yielded by the classical joint maximum likelihood interpretation (e.g., as found in the work by Paxman et al.). Finally, our theoretical analysis is illustrated through simulated problems. Jérôme Idier, Laurent M. Mugnier, Amandine Blanc |
IEEE Trans. Image Process. | 3 |