Technical Section: Hyper-Resolution: Image detail reconstruction through parametric edges

Authors:
Lijun Yin;Matt Yourst
Affiliations:
Department of Computer Science, State University of New York at Binghamton, Binghamton, NY 13902, USA;Department of Computer Science, State University of New York at Binghamton, Binghamton, NY 13902, USA
Venue:
Computers and Graphics
Year:
2005

Citing 18
Cited 2

A Computational Approach to Edge Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Curves and surfaces for computer aided geometric design: a practical guide

Curves and surfaces for computer aided geometric design: a practical guide
Super-Resolution Reconstruction of Image Sequences

IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Low-Level Vision

International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Image Editing in the Contour Domain

IEEE Transactions on Pattern Analysis and Machine Intelligence
Image analogies

Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Generating realistic facial expressions with wrinkles for model-based coding

Computer Vision and Image Understanding
Example-Based Super-Resolution

IEEE Computer Graphics and Applications
Face Recognition: Features Versus Templates

IEEE Transactions on Pattern Analysis and Machine Intelligence
Limits on Super-Resolution and How to Break Them

IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion Deblurring and Super-resolution from an Image Sequence

ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Assorted Pixels: Multi-sampled Imaging with Structural Models

ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Space Scale Localization, Blur, and Contour-Based Image Coding

CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
3D face recognition based on high-resolution 3D face modeling from frontal and profile views

WBMA '03 Proceedings of the 2003 ACM SIGMM workshop on Biometrics methods and applications
Silhouette maps for improved texture magnification

Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
A computationally efficient superresolution image reconstruction algorithm

IEEE Transactions on Image Processing
Recursive high-resolution reconstruction of blurred multiframe images

IEEE Transactions on Image Processing
Feature-based textures

EGSR'04 Proceedings of the Fifteenth Eurographics conference on Rendering Techniques

Low-resolution gait recognition

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
Image super-resolution by curve fitting in the threshold decomposition domain

Journal of Visual Communication and Image Representation

Quantified Score

Hi-index	0.00

Visualization

Abstract

Hyper-Resolution, a new technique for super-resolution reconstruction of images, is based on matching low-resolution target image details to their high-resolution counterparts from an image database. Central to the algorithm is a novel transform of image content from the orthogonal pixel space to a parametric space structured around edges. This approach offers improved quality, more flexibility and significantly faster performance than previous work in the field. Implementation strategies for achieving this efficiency are carefully outlined. The algorithm is evaluated by controlled assessment, qualitative evaluation, and applications to facial detail reconstruction and identification. The algorithm is finally analyzed through the comparison with alternative techniques.