Robust dynamic range computation for high dynamic range content
Authors: Hulusic, V., Valenzise, G., Debattista, K. and Dufaux, F.
Journal: IS and T International Symposium on Electronic Imaging Science and Technology
Pages: 151-155
eISSN: 2470-1173
DOI: 10.2352/ISSN.2470-1173.2017.14.HVEI-135
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.
https://eprints.bournemouth.ac.uk/30370/
Source: Scopus
Robust dynamic range computation for high dynamic range content
Authors: Hulusic, V., Valenzise, G., Debattista, K. and Dufaux, F.
Journal: Human Vision and Electronic Imaging Conference, IS&T International Symposium on Electronic Imaging (EI 2017)
https://eprints.bournemouth.ac.uk/30370/
Source: Manual
Robust dynamic range computation for high dynamic range content
Authors: Hulusic, V., Valenzise, G., Debattista, K. and Dufaux, F.
Conference: HVEI 2017 : IS&T Conference on Human Vision and Electronic Imaging
Pages: 151-155
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.
https://eprints.bournemouth.ac.uk/30370/
Source: BURO EPrints