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Shin Yoshimura

dblp:51/3383 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2008
—ORCID · none

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

Artificial intelligence and machine learning · 1Graphics, 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 · 78% Geometric modeling and processing · 22%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing
image registration
0.112008
Super-resolution from image sequence under influence of hot-air optical turbulence · CVPR 2008
Image and video processing › super-resolution
multi-frame super-resolution
0.112008
Super-resolution from image sequence under influence of hot-air optical turbulence · CVPR 2008
Geometric modeling and processing › registration
non-rigid registration
0.112008
Super-resolution from image sequence under influence of hot-air optical turbulence · CVPR 2008
Image and video processing
super-resolution
0.112008
Super-resolution from image sequence under influence of hot-air optical turbulence · CVPR 2008
Image and video processing › image restoration › adverse weather image restoration
atmospheric turbulence mitigation
0.012008
Super-resolution from image sequence under influence of hot-air optical turbulence · CVPR 2008
Image and video processing
image restoration
0.012008
Super-resolution from image sequence under influence of hot-air optical turbulence · CVPR 2008

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

non-rigid registration · 0.1b-spline deformation model · 0.1
YearPublicationVenuePosition
2008 Super-resolution from image sequence under influence of hot-air optical turbulence
abstract
The appearance of a distant object, when viewed through a telephoto-lens, is often deformed nonuniformly by the influence of hot-air optical turbulence. The deformation is unsteady: an image sequence can include nonuniform movement of the object even if a stationary camera is used for a static object. This study proposes a multi-frame super-resolution reconstruction from such an image sequence. The process consists of the following three stages. In the first stage, an image frame without deformation is estimated from the sequence. However, there is little detailed information about the object. In the second stage, each frame in the sequence is aligned non-rigidly to the estimated image using a non-rigid deformation model. A stable non-rigid registration technique with a B-spline function is also proposed in this study for dealing with a textureless region. In the third stage, a multi-frame super-resolution reconstruction using the non-rigid deformation recovers the detailed information in the frame obtained in the first stage. Experiments using synthetic images demonstrate the accuracy and stability of the proposed non-rigid registration technique. Furthermore, experiments using real sequences underscore the effectiveness of the proposed process.
Masao Shimizu, Shin Yoshimura, Masayuki Tanaka 0001, Masatoshi Okutomi
CVPR2