Detail-Enhanced Multi-Scale Exposure Fusion

Detail-Enhanced Multi-Scale Exposure Fusion
Title:
Detail-Enhanced Multi-Scale Exposure Fusion
Other Titles:
IEEE Transactions on Image Processing
Keywords:
Publication Date:
01 March 2017
Citation:
Z. Li, Z. Wei, C. Wen and J. Zheng, "Detail-Enhanced Multi-Scale Exposure Fusion," in IEEE Transactions on Image Processing, vol. 26, no. 3, pp. 1243-1252, March 2017. doi: 10.1109/TIP.2017.2651366
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.
License type:
PublisherCopyrights
Funding Info:
Description:
(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
ISSN:
1057-7149
1941-0042
Files uploaded: