DocumentCode
3327860
Title
On the perceptual similarity of realistic looking tone mapped High Dynamic Range images
Author
Barkowsky, Marcus ; Le Callet, Patrick
Author_Institution
Polytech´´ Nantes, Nantes, France
fYear
2010
fDate
26-29 Sept. 2010
Firstpage
3245
Lastpage
3248
Abstract
High Dynamic Range (HDR) images are usually displayed on conventional Low Dynamic Range (LDR) displays because of the limited availability of HDR displays. For the conversion of the large dynamic luminance range into the eight bit quantized values, parameterized Tone Mapping Operators (TMO) are applied. Human observers are able to optimize the parameters in order to get the highest Quality of Experience by judging the displayed LDR images on a realism scale. In the study presented in this paper, two TMOs with three parameters each were evaluated by observers in a subjective experiment. Although the chosen parameter settings vary largely, the chosen images appear to have the same QoE for the observers. In order to assess this similarity objectively, three commonly used image quality measurement algorithms were applied. Their agreement with the preference of the observers was analyzed and it was found that the Visual Difference Predictor (VDP) outperforms the Structural Similarity Index and the Root Mean Square Error. A threshold value for VDP is derived that indicates when two LDR images appear to have the same Quality of Experience.
Keywords
data compression; image coding; eight bit quantized values; high dynamic range images; image quality; low dynamic range displays; perceptual similarity; realistic looking tone; tone mapping operators; visual difference predictor; Algorithm design and analysis; Dynamic range; Humans; Image quality; Observers; Pixel; Prediction algorithms; High Dynamic Range; Objective Image Quality; Quality of Experience; Subjective Experiment; Tone Mapping Operators;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location
Hong Kong
ISSN
1522-4880
Print_ISBN
978-1-4244-7992-4
Electronic_ISBN
1522-4880
Type
conf
DOI
10.1109/ICIP.2010.5651143
Filename
5651143
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