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Reconstruction of high dynamic range images with poisson noise modeling and integrated denoising

Bart Goossens (UGent) , Hiep Luong (UGent) , Jan Aelterman (UGent) , Aleksandra Pizurica (UGent) and Wilfried Philips (UGent)
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Abstract
In this paper, we present a new method for High Dynamic Range (HDR) reconstruction based on a set of multiple photographs with different exposure times. While most existing techniques take a deterministic approach by assuming that the acquired low dynamic range (LDR) images are noise-free, we explicitly model the photon arrival process by assuming sensor data corrupted by Poisson noise. Taking the noise characteristics of the sensor data into account leads to a more robust way to estimate the non-parametric camera response function (CRF) compared to existing techniques. To further improve the HDR reconstruction, we adopt the split-Bregman framework and use Total Variation for regularization. Experimental results on real camera images and ground-truth data show the effectiveness of the proposed approach.
Keywords
High dynamic range imaging, denoising, CAMERA RESPONSE

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Chicago
Goossens, Bart, Hiep Luong, Jan Aelterman, Aleksandra Pizurica, and Wilfried Philips. 2011. “Reconstruction of High Dynamic Range Images with Poisson Noise Modeling and Integrated Denoising.” In IEEE International Conference on Image Processing ICIP, 3429–3432. Piscataway, NJ, USA: IEEE.
APA
Goossens, B., Luong, H., Aelterman, J., Pizurica, A., & Philips, W. (2011). Reconstruction of high dynamic range images with poisson noise modeling and integrated denoising. IEEE International Conference on Image Processing ICIP (pp. 3429–3432). Presented at the 18th IEEE International conference on Image Processing (ICIP 2011), Piscataway, NJ, USA: IEEE.
Vancouver
1.
Goossens B, Luong H, Aelterman J, Pizurica A, Philips W. Reconstruction of high dynamic range images with poisson noise modeling and integrated denoising. IEEE International Conference on Image Processing ICIP. Piscataway, NJ, USA: IEEE; 2011. p. 3429–32.
MLA
Goossens, Bart, Hiep Luong, Jan Aelterman, et al. “Reconstruction of High Dynamic Range Images with Poisson Noise Modeling and Integrated Denoising.” IEEE International Conference on Image Processing ICIP. Piscataway, NJ, USA: IEEE, 2011. 3429–3432. Print.
@inproceedings{2015257,
  abstract     = {In this paper, we present a new method for High Dynamic Range (HDR) reconstruction based on a set of multiple photographs with different exposure times. While most existing techniques take a deterministic approach by assuming that the acquired low dynamic range (LDR) images are noise-free, we explicitly model the photon arrival process by assuming sensor data corrupted by Poisson noise. Taking the noise characteristics of the sensor data into account leads to a more robust way to estimate the non-parametric camera response function (CRF) compared to existing techniques. To further improve the HDR reconstruction, we adopt the split-Bregman framework and use Total Variation for regularization. Experimental results on real camera images and ground-truth data show the effectiveness of the proposed approach.},
  author       = {Goossens, Bart and Luong, Hiep and Aelterman, Jan and Pizurica, Aleksandra and Philips, Wilfried},
  booktitle    = {IEEE International Conference on Image Processing ICIP},
  isbn         = {9781457713033},
  issn         = {1522-4880},
  language     = {eng},
  location     = {Brussels, Belgium},
  pages        = {3429--3432},
  publisher    = {IEEE},
  title        = {Reconstruction of high dynamic range images with poisson noise modeling and integrated denoising},
  url          = {http://dx.doi.org/10.1109/ICIP.2011.6116449},
  year         = {2011},
}

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