Literature DB >> 32310768

Fast Multi-Scale Structural Patch Decomposition for Multi-Exposure Image Fusion.

Hui Li, Kede Ma, Hongwei Yong, Lei Zhang.   

Abstract

Exposure bracketing is crucial to high dynamic range imaging, but it is prone to halos for static scenes and ghosting artifacts for dynamic scenes. The recently proposed structural patch decomposition for multi-exposure fusion (SPD-MEF) has achieved reliable performance in deghosting, but suffers from visible halo artifacts and is computationally expensive. In addition, its relationship to other MEF methods is unclear. We show that without explicitly performing structural patch decomposition, we arrive at an unnormalized version of SPD-MEF, which enjoys an order of 30× speed-up, and is closely related to pixel-level MEF methods as well as the standard two-layer decomposition method for MEF. Moreover, we develop a fast multi-scale SPD-MEF method, which can effectively reduce halo artifacts. Experimental results demonstrate the effectiveness of the proposed MEF method in terms of speed and quality.

Entities:  

Year:  2020        PMID: 32310768     DOI: 10.1109/TIP.2020.2987133

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


  2 in total

1.  General Image Fusion for an Arbitrary Number of Inputs Using Convolutional Neural Networks.

Authors:  Yifan Xiao; Zhixin Guo; Peter Veelaert; Wilfried Philips
Journal:  Sensors (Basel)       Date:  2022-03-23       Impact factor: 3.576

2.  Multi-Exposure Image Fusion Algorithm Based on Improved Weight Function.

Authors:  Ke Xu; Qin Wang; Huangqing Xiao; Kelin Liu
Journal:  Front Neurorobot       Date:  2022-03-08       Impact factor: 2.650

  2 in total

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