Abstract
Conventional inverse tone-mapping (ITM) methods tend to produce contrast distortions such as contrast loss and contrast reversal in reconstructed high dynamic range (HDR) images. This paper proposes a novel ITM optimization framework based on the assumption that the input low dynamic range (LDR) image is similar to the LDR image obtained by tone mapping a true HDR image. In the proposed framework, an HDR image is initially reconstructed by applying a conventional tone-mapping function in a reverse manner, and then the reconstructed HDR image is iteratively modified toward the optimum HDR image by minimizing the difference between the input LDR image and a tone-mapped LDR image obtained from the reconstructed HDR image. The experimental results demonstrate that the proposed framework effectively reconstructs a high-quality HDR image and outperforms other conventional methods in terms of objective quality.
Original language | English |
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Pages (from-to) | 274-283 |
Number of pages | 10 |
Journal | Signal Processing: Image Communication |
Volume | 78 |
DOIs | |
Publication status | Published - 2019 Oct |
Bibliographical note
Funding Information:This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) ( 2017-0-00250 , Intelligent Defense Boundary Surveillance Technology Using Collaborative Reinforced Learning of Embedded Edge Camera and Image Analysis).
Publisher Copyright:
© 2019
Keywords
- Brightness enhancement function
- Inverse tone mapping
- Newton–Raphson
ASJC Scopus subject areas
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering