A Discretize-then-Optimize Approach to Super-Resolution Reconstruction and Motion Estimation

  • Eric Ng University of Ontario Institute of Technology
  • Mehran Ebrahimi University of Ontario Institute of Technology

Abstract

The process of recovering a high-resolution (HR) image from a set
of distorted (i.e. deformed, blurry, noisy, etc.) low-resolution (LR) images
is known as super-resolution. Super-resolution problem will require
the reconstruction of the HR image and estimations of motion
between LR images. In this study, image reconstruction and motion
estimation will be treated as a coupled problem. The proposed algorithm
uses an inverse model followed by a discretize-then-optimize
approach. Preliminary experiments on test data will be presented.

Published
2015-12-15
How to Cite
Ng, E., & Ebrahimi, M. (2015). A Discretize-then-Optimize Approach to Super-Resolution Reconstruction and Motion Estimation. Journal of Computational Vision and Imaging Systems, 1(1). https://doi.org/10.15353/vsnl.v1i1.39
Section
Articles