Gradient field multi-exposure images fusion for high dynamic range image visualization

Authors:
Bo Gu;Wujing Li;Jiangtao Wong;Minyun Zhu;Minghui Wang
Affiliations:
College of Computer Science, Sichuan University, Chengdu, China;College of Computer Science, Sichuan University, Chengdu, China;College of Computer and Information Engineering, Guangxi Teachers Education University, Guangxi, China;College of Computer Science, Sichuan University, Chengdu, China;College of Computer Science, Sichuan University, Chengdu, China
Venue:
Journal of Visual Communication and Image Representation
Year:
2012

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Abstract

This paper presents a novel method for fusing multi-exposure images into a low dynamic range (LDR) image that is suitable for display and visualization but it contains details in the high dynamic range (HDR) counterpart. Fused gradient field is derived from the structure tensor of inputs based on multi-dimensional Riemannian geometry with a Euclidean metric assumed. Afterwards, a new method is proposed for modifying the gradient field iteratively with twice average filtering and nonlinearly compressing in multi-scales. These modification operations are all done at the finest resolution. The result is obtained through solving a Poisson equation then linearly stretching to the common range. Experimental results demonstrate the efficiency and effectiveness of this method.