English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

A point-spread function describes the optics of an imaging system and can beused to correct collected images for instrumental effects. The state of the artfor deconvolving images with the point-spread function is the Richardson-Lucyalgorithm; however, despite its high fidelity, it is slow and cannot accountfor light scattered out of the field of view of the detector. We reinstate theBasic Iterative Deconvolution (BID) algorithm, a deconvolution algorithm thatconsiders photons scattered out of the field of view of the detector, andextend it for image subregion deconvolutions. Its runtime is 1.8 to 7.1 fasterthan the Richardson-Lucy algorithm for 4096 x 4096 pixels images and up to anadditional factor of 150 for subregions of 250 x 250 pixels. We test theextended BID algorithm for solar images taken by the Atmospheric ImagingAssembly (AIA), and find that the deviations between the reconstructedintensities of BID and the Richardson-Lucy algorithm are smaller than 1% + 0.1DN.

The Basic Iterative Deconvolution: A fast instrumental point-spread  function deconvolution method that corrects for light that is scattered out  of the field of view of a detector