In:
Scientific Reports, Springer Science and Business Media LLC, Vol. 12, No. 1 ( 2022-07-04)
Abstract:
We present a fast and simple algorithm for super-resolution with single images. It is based on penalized least squares regression and exploits the tensor structure of two-dimensional convolution. A ridge penalty and a difference penalty are combined; the former removes singularities, while the latter eliminates ringing. We exploit the conjugate gradient algorithm to avoid explicit matrix inversion. Large images are handled with ease: zooming a 100 by 100 pixel image to 800 by 800 pixels takes less than a second on an average PC. Several examples, from applications in wide-field fluorescence microscopy, illustrate performance.
Type of Medium:
Online Resource
ISSN:
2045-2322
DOI:
10.1038/s41598-022-14874-8
Language:
English
Publisher:
Springer Science and Business Media LLC
Publication Date:
2022
detail.hit.zdb_id:
2615211-3
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