C++ implementation of several image contrast enhancement techniques.
- AINDANE
- Adaptive and integrated neighborhood-dependent approach for nonlinear enhancement of color images (2005), Tao et al.
- Accepted input image : Color(√) Grayscale(×)
- Only OpenCV3 is needed.
- WTHE
- Fast image/video contrast enhancement based on weighted thresholded histogram equalization (2007), Wang et al.
- Accepted input image : Color(√) Grayscale(√)
- Only OpenCV3 is needed.
- GCEHistMod
- A histogram modification framework and its application for image contrast enhancement (TIP 2009), Arici et al.
- Accepted input image : Color(√) Grayscale(√)
- Only OpenCV3 is needed.
- LDR
- Contrast Enhancement based on Layered Difference Representation of 2D Histograms (TIP 2013), Lee et al.
- Accepted input image : Color(√) Grayscale(√)
- Only OpenCV3 is needed.
- AGCWD
- Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution (TIP 2013), Huang et al.
- Accepted input image : Color(√) Grayscale(√)
- Only OpenCV3 is needed.
- AGCIE
- An adaptive gamma correction for image enhancement (2016), Rahman et al.
- Accepted input image : Color(√) Grayscale(√)
- Only OpenCV3 is needed.
- IAGCWD
- Contrast enhancement of brightness-distorted images by improved adaptive gamma correction (2017), Cao et al.
- Accepted input image : Color(√) Grayscale(√)
- Only OpenCV3 is needed.
- Ying_2017_CAIP
- A New Image Contrast Enhancement Algorithm Using Exposure Fusion Framework (CAIP 2017), Ying et al.
- Accepted input image : Color(√) Grayscale(√)
- All requirements are needed.
- CEusingLuminanceAdaptation
- Retinex-based perceptual contrast enhancement in images using luminance adaptation (2018), Fu et al.
- Accepted input image : Color(√) Grayscale(×)
- Only OpenCV3 is needed.
- adaptiveImageEnhancement
- Adaptive image enhancement method for correcting low-illumination images (2019), Wang et al.
- Accepted input image : Color(√) Grayscale(×)
- Only OpenCV3 is needed.
- JHE
- A novel joint histogram equalization based image contrast enhancement (2019), Agrawal et al.
- Accepted input image : Color(√) Grayscale(√)
- Only OpenCV3 is needed.
- SEF
- An Extended Exposure Fusion and its Application to Single Image Contrast Enhancement (WACV 2020), Hessel et al.
- Accepted input image : Color(√) Grayscale(√)
- Only OpenCV3 is needed.
- Ubuntu-16.04
- Cmake
- OpenCV-3.4.6+
- Dlib-19.18+
- SuperLU-5.2.1+
- Armadillo-9.800.3+
- Before install Armadillo, SuperLU 5 must be installed.
cd Image-Contrast-Enhancement
cmake .
make
./main <input_image>
@article{tao2005adaptive,
title={Adaptive and integrated neighborhood-dependent approach for nonlinear enhancement of color images},
author={Tao, Li and Asari, Vijayan K},
journal={Journal of Electronic Imaging},
volume={14},
number={4},
pages={043006},
year={2005},
publisher={International Society for Optics and Photonics}
}
@article{wang2007fast,
title={Fast image/video contrast enhancement based on weighted thresholded histogram equalization},
author={Wang, Qing and Ward, Rabab K},
journal={IEEE transactions on Consumer Electronics},
volume={53},
number={2},
pages={757--764},
year={2007},
publisher={IEEE}
}
@article{arici2009histogram,
title={A histogram modification framework and its application for image contrast enhancement},
author={Arici, Tarik and Dikbas, Salih and Altunbasak, Yucel},
journal={IEEE Transactions on image processing},
volume={18},
number={9},
pages={1921--1935},
year={2009},
publisher={IEEE}
}
@article{lee2013contrast,
title={Contrast enhancement based on layered difference representation of 2D histograms},
author={Lee, Chulwoo and Lee, Chul and Kim, Chang-Su},
journal={IEEE transactions on image processing},
volume={22},
number={12},
pages={5372--5384},
year={2013},
publisher={IEEE}
}
@article{huang2013efficient,
title={Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution},
author={Huang, Shihchia and Cheng, Fanchieh and Chiu, Yisheng},
journal={IEEE Transactions on Image Processing},
volume={22},
number={3},
pages={1032--1041},
year={2013}
}
@article{rahman2016an,
title={An adaptive gamma correction for image enhancement},
author={Rahman, Shanto and Rahman, Mostafijur and Abdullahalwadud, M and Alquaderi, Golam Dastegir and Shoyaib, Mohammad},
journal={Eurasip Journal on Image and Video Processing},
volume={2016},
number={1},
pages={35},
year={2016}
}
@article{cao2017contrast,
title={Contrast enhancement of brightness-distorted images by improved adaptive gamma correction},
author={Cao, Gang and Huang, Lihui and Tian, Huawei and Huang, Xianglin and Wang, Yongbin and Zhi, Ruicong},
journal={Computers & Electrical Engineering},
volume={66},
pages={569--582},
year={2017}
}
@inproceedings{ying2017new,
title={A New Image Contrast Enhancement Algorithm Using Exposure Fusion Framework},
author={Ying, Zhenqiang and Li, Ge and Ren, Yurui and Wang, Ronggang and Wang, Wenmin},
booktitle={International Conference on Computer Analysis of Images and Patterns},
pages={36--46},
year={2017},
organization={Springer}
}
@article{fu2018retinex,
title={Retinex-based perceptual contrast enhancement in images using luminance adaptation},
author={Fu, Qingtao and Jung, Cheolkon and Xu, Kaiqiang},
journal={IEEE Access},
volume={6},
pages={61277--61286},
year={2018},
publisher={IEEE}
}
@article{wang2019adaptive,
title={Adaptive image enhancement method for correcting low-illumination images},
author={Wang, Wencheng and Chen, Zhenxue and Yuan, Xiaohui and Wu, Xiaojin},
journal={Information Sciences},
volume={496},
pages={25--41},
year={2019},
publisher={Elsevier}
}
@article{agrawal2019novel,
title={A novel joint histogram equalization based image contrast enhancement},
author={Agrawal, Sanjay and Panda, Rutuparna and Mishro, PK and Abraham, Ajith},
journal={Journal of King Saud University-Computer and Information Sciences},
year={2019},
publisher={Elsevier}
}
@inproceedings{hessel2020extended,
title={An extended exposure fusion and its application to single image contrast enhancement},
author={Hessel, Charles and Morel, Jean-Michel},
booktitle={The IEEE Winter Conference on Applications of Computer Vision},
pages={137--146},
year={2020}
}