Intelligent detail enhancement for differently exposed images

Intelligent detail enhancement for differently exposed images
Title:
Intelligent detail enhancement for differently exposed images
Other Titles:
2017 IEEE International Conference on Image Processing (ICIP)
Keywords:
Publication Date:
17 September 2017
Citation:
F. Kou, W. Chen, X. Wu and Z. Li, "Intelligent detail enhancement for differently exposed images," 2017 IEEE International Conference on Image Processing (ICIP), Beijing, China, 2017, pp. 3185-3189. doi: 10.1109/ICIP.2017.8296870
Abstract:
Multi-scale exposure fusion is a fast approach to fuse several differently exposed images captured at the same high dynamic range (HDR) scene into a high quality low dynamic range (LDR) image. The fused image is expected to include all details of the input images, however, the details in the brightest and darkest regions are usually not preserved well. Adding details that are extracted from the input images to the fused image is an efficient approach to overcome the problem. In this paper, a fast selectively detail enhancement algorithm is proposed to extract the details in the brightest and darkest regions of the HDR scene and add the extracted details to the fused image. Experimental results show that the proposed algorithm can enhance the details of the fused image much faster than the existing algorithms with comparable or even better visual quality.
License type:
PublisherCopyrights
Funding Info:
Description:
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.
ISSN:
2381-8549
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