title: QoE-based multi-exposure fusion in hierarchical multivariate Gaussian CRF.
abstract: Many state-of-the-art fusion methods, combining details in images taken under different exposures into one well-exposed image, can be found in the literature. However, insufficient study has been conducted to explore how perceptual factors can provide viewers better quality of experience on fused images. We propose two perceptual quality measures: perceived local contrast and color saturation, which are embedded in our novel hierarchical multivariate Gaussian conditional random field model, to illustrate improved performance for multi-exposure fusion. We show that our method generates images with better quality than existing methods for a variety of scenes.
authors.affiliation: Department of Computing Science, University of Alberta, Edmonton, AB T6G 2E8, Canada. rshen@ualberta.ca
authors.forename: Rui
authors.initials: R
authors.lastname: Shen
authors.forename: Irene
authors.initials: I
authors.lastname: Cheng
authors.forename: Anup
authors.initials: A
authors.lastname: Basu