Abstract
Systems that do not meet the requirements of the sampling theorem produce images corrupted by aliasing. Higher resolution images are attainable by unfolding aliased spatial frequencies. Multiple-image super-resolution has seen much attention in the literature though with no clear optimum algorithm for many real-world applications. We propose a method of multiframe super-resolution using a set of convolutional sinc kernels, tailored to the specific shifts between images, capable of resolving up to the diffraction limit. We demonstrate our method for the case of global shifts before we treat a pixel-level super-resolution.
© 2019 Optical Society of America
Full Article |
PDF Article
More Like This
Cited By
You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Login to access Optica Member Subscription
Figures (7)
You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Login to access Optica Member Subscription
Tables (2)
You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Login to access Optica Member Subscription
Equations (20)
You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Login to access Optica Member Subscription