Contrast Sensitivity Based Multiscale Base–Detail Separation for Enhanced HDR Imaging
Clicks: 182
ID: 110758
2020
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
182 views
19 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #149 of 187 articles by views in applied sciences
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 187 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
High dynamic range (HDR) imaging is used to represent scenes with a greater dynamic range of luminance on a standard dynamic range display. Usually, HDR images are synthesized through base–detail separations. The base layer is used for tone compression and the detail layer is used for detail preservation. The representative detail-preserved algorithm iCAM06 has a tendency to reduce the sharpness of dim surround images, because of the fixed edge-stopping function of the fast-bilateral filter (FBF). This paper proposes a novel base–detail separation and detail compensation technique using the contrast sensitivity function (CSF) in the segmented frequency domain. Experimental results show that the proposed rendering method has better sharpness features and image quality than previous methods correlated by the human visual system.
| Reference Key |
kwon2020appliedcontrast
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Hyuk-Ju Kwon;Sung-Hak Lee;Kwon, Hyuk-Ju;Lee, Sung-Hak; |
| Journal | applied sciences |
| Year | 2020 |
| DOI |
10.3390/app10072513
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.