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Trained Perceptual Transform for Quality Assessment of High Dynamic Range Images and Video

Accepted version
Peer-reviewed

Type

Conference Object

Change log

Authors

Ye, N 
Perez-Ortiz, M 
Mantiuk, RK 

Abstract

In this paper, we propose a trained perceptually transform for quality assessment of high dynamic range (HDR) images and video. The transform is used to convert absolute luminance values found in HDR images into perceptually uniform units, which can be used with any standard-dynamic-range metric. The new transform is derived by fitting the parameters of a previously proposed perceptual encoding function to 4 different HDR subjective quality assessment datasets using Bayesian optimization. The new transform combined with a simple peak signal-to-noise ratio measure achieves better prediction performance in cross-dataset validation than existing transforms. We provide Matlab code for our metric

Description

Keywords

Image quality assessment, high dynamic range, perceptually uniform encoding

Journal Title

Proceedings - International Conference on Image Processing, ICIP

Conference Name

2018 25th IEEE International Conference on Image Processing (ICIP)

Journal ISSN

1522-4880

Volume Title

Publisher

IEEE
Sponsorship
European Research Council (725253)