Abstract
Automatic contrast enhancement using reversible data hiding (ACERDH) has been found to be useful in automatic image enhancement field. Instead of just providing data hiding ability, ACERDH also equalizes the pixel histogram as a part of data hiding process. This allows original image recovery directly from the enhanced image, without any additional data, which provides file saving feature by not having to save the original image. In this paper, we propose two improvements and two novel distortion minimization methods for ACERDH [1] method. The experimental results show that the proposed method has higher embedding capacity and lower distortion than ACERDH.
Original language | English |
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Title of host publication | 2019 IEEE 4th International Conference on Image, Vision and Computing, ICIVC 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 291-295 |
Number of pages | 5 |
ISBN (Electronic) | 9781728123257 |
DOIs | |
Publication status | Published - 2019 Jul |
Event | 4th IEEE International Conference on Image, Vision and Computing, ICIVC 2019 - Xiamen, China Duration: 2019 Jul 5 → 2019 Jul 7 |
Publication series
Name | 2019 IEEE 4th International Conference on Image, Vision and Computing, ICIVC 2019 |
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Conference
Conference | 4th IEEE International Conference on Image, Vision and Computing, ICIVC 2019 |
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Country/Territory | China |
City | Xiamen |
Period | 19/7/5 → 19/7/7 |
Bibliographical note
Funding Information:ACKNOWLEDGMENT This work was supported by the National Research Foundation of Korea grant funded by the Korea government (MEST) (No.NRF-2019R1I1A1A01059582) and supported by Institute for Information & communications Technology Promotion grant funded by the Korea government (MSIP) (No.2018-0-00365, Development of on-off hybrid blockchain technology for real-time large-scale data distribution).
Publisher Copyright:
© 2019 IEEE.
Keywords
- automatic contrast enhancement
- reversible data hiding
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Signal Processing
- Media Technology