Back to articles
Articles
Volume: 29 | Article ID: art00019
Image
Robust Dynamic Range Computation for High Dynamic Range Content
  DOI :  10.2352/ISSN.2470-1173.2017.14.HVEI-135  Published OnlineJanuary 2017
Abstract

High dynamic range (HDR) imaging has become an important topic in both academic and industrial domains. Nevertheless, the concept of dynamic range (DR), which underpins HDR, and the way it is measured are still not clearly understood. The current approach to measure DR results in a poor correlation with perceptual scores (r ≈ 0.6). In this paper, we analyze the limitations of the existing DR measure, and propose several options to predict more accurately subjective DR judgments. Compared to the traditional DR estimates, the proposed measures show significant improvements in Spearman's and Pearson's correlations with subjective data (up to r ≈ 0.9). Despite their straightforward nature, these improvements are particularly evident in specific cases, where the scores obtained by using the classical measure have the highest error compared to the perceptual mean opinion score.

Subject Areas :
Views 23
Downloads 0
 articleview.views 23
 articleview.downloads 0
  Cite this article 

Vedad Hulusic, Giuseppe Valenzise, Kurt Debattista, Frédéric Dufaux, "Robust Dynamic Range Computation for High Dynamic Range Contentin Proc. IS&T Int’l. Symp. on Electronic Imaging: Human Vision and Electronic Imaging,  2017,  pp 151 - 155,  https://doi.org/10.2352/ISSN.2470-1173.2017.14.HVEI-135

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2017
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology