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

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• 作者：Bo Gu^a ; ^{goobo@163.com} ; Wujing Li^a ; ^{liwujing12345@gmail.com} ; Jiangtao Wong^b ; ^{prognosis@163.com} ; Minyun Zhu^a ; ^{zhuminyun88@126.com} ; Minghui Wang^a ; ^{wangminghui@scu.edu.cn}
• 关键词：Image fusion ; Image gradient ; Multi-exposure ; HDR ; Riemannian manifold ; Structure tensor ; Gradient modification ; Dynamic range compression
• 刊名：Journal of Visual Communication and Image Representation
• 出版年：2012
• 期刊代码：141_10473203
• 类别：cp
• 出版时间：May, 2012
• 卷：23
• 期：4
• 页码：604-610
• 文件大小：2487 K

摘要

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.