Literature DB >> 23288338

QoE-based multi-exposure fusion in hierarchical multivariate Gaussian CRF.

Rui Shen1, Irene Cheng, Anup Basu.   

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.

Entities:  

Year:  2013        PMID: 23288338     DOI: 10.1109/TIP.2012.2236346

Source DB:  PubMed          Journal:  IEEE Trans Image Process        ISSN: 1057-7149            Impact factor:   10.856


  2 in total

1.  Multi-scale pixel-based image fusion using multivariate empirical mode decomposition.

Authors:  Naveed ur Rehman; Shoaib Ehsan; Syed Muhammad Umer Abdullah; Muhammad Jehanzaib Akhtar; Danilo P Mandic; Klaus D McDonald-Maier
Journal:  Sensors (Basel)       Date:  2015-05-08       Impact factor: 3.576

2.  A Novel Multi-Exposure Image Fusion Method Based on Adaptive Patch Structure.

Authors:  Yuanyuan Li; Yanjing Sun; Mingyao Zheng; Xinghua Huang; Guanqiu Qi; Hexu Hu; Zhiqin Zhu
Journal:  Entropy (Basel)       Date:  2018-12-06       Impact factor: 2.524

  2 in total

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