Literature DB >> 28092537

Detail-Enhanced Multi-Scale Exposure Fusion.

Zhengguo Li, Zhe Wei, Changyun Wen, Jinghong Zheng.   

Abstract

Multi-scale exposure fusion is an effective image enhancement technique for a high dynamic range (HDR) scene. In this paper, a new multi-scale exposure fusion algorithm is proposed to merge differently exposed low dynamic range (LDR) images by using the weighted guided image filter to smooth the Gaussian pyramids of weight maps for all the LDR images. Details in the brightest and darkest regions of the HDR scene are preserved better by the proposed algorithm without relative brightness change in the fused image. In addition, a new weighted structure tensor is introduced to the differently exposed images and it is adopted to design a detail extraction component for the proposed fusion algorithm, such that users are allowed to manipulate fine details in the enhanced image according to their preference. The proposed multi-scale exposure fusion algorithm is also applied to design a simple single image brightening algorithm for both low-light imaging and back-light imaging.

Year:  2017        PMID: 28092537     DOI: 10.1109/TIP.2017.2651366

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


  4 in total

1.  An Adaptive Exposure Fusion Method Using fuzzy Logic and Multivariate Normal Conditional Random Fields.

Authors:  Yu-Hsiu Lin; Kai-Lung Hua; Hsin-Han Lu; Wei-Lun Sun; Yung-Yao Chen
Journal:  Sensors (Basel)       Date:  2019-10-31       Impact factor: 3.576

2.  Two-Exposure Image Fusion Based on Optimized Adaptive Gamma Correction.

Authors:  Yan-Tsung Peng; He-Hao Liao; Ching-Fu Chen
Journal:  Sensors (Basel)       Date:  2021-12-22       Impact factor: 3.576

3.  Multi-scale Fusion of Stretched Infrared and Visible Images.

Authors:  Weibin Jia; Zhihuan Song; Zhengguo Li
Journal:  Sensors (Basel)       Date:  2022-09-02       Impact factor: 3.847

4.  Efficient joint noise removal and multi exposure fusion.

Authors:  Antoni Buades; Jose Luis Lisani; Onofre Martorell
Journal:  PLoS One       Date:  2022-03-25       Impact factor: 3.240

  4 in total

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