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 |
|---|---|
| Pages (from-to) | 274-283 |
| Number of pages | 10 |
| Journal | Signal Processing: Image Communication |
| Volume | 78 |
| DOIs | |
| Publication status | Published - 2019 Oct 1 |
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
Cite this
An optimization framework for inverse tone mapping using a single low dynamic range image. / Fan, Ming; Lee, Dae Hong; Kim, Seung Wook; Ko, Sung-Jea.
In: Signal Processing: Image Communication, Vol. 78, 01.10.2019, p. 274-283.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - An optimization framework for inverse tone mapping using a single low dynamic range image
AU - Fan, Ming
AU - Lee, Dae Hong
AU - Kim, Seung Wook
AU - Ko, Sung-Jea
PY - 2019/10/1
Y1 - 2019/10/1
N2 - 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.
AB - 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.
KW - Brightness enhancement function
KW - Inverse tone mapping
KW - Newton–Raphson
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U2 - 10.1016/j.image.2019.07.009
DO - 10.1016/j.image.2019.07.009
M3 - Article
AN - SCOPUS:85069839917
VL - 78
SP - 274
EP - 283
JO - Signal Processing: Image Communication
JF - Signal Processing: Image Communication
SN - 0923-5965
ER -