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http://dx.doi.org/10.9717/kmms.2019.22.1.010

Noise Reduction of HDR Detail Layer Using a Kalman Filter Adapted to Local Image Activity  

Kim, Tae-Kyu (School of Electronics Engineering, Kyungpook National University)
Song, Inho (School of Electronics Engineering, Kyungpook National University)
Lee, Sung-Hak (School of Electronics Engineering, Kyungpook National University)
Publication Information
Journal of Korea Multimedia Society / v.22, no.1, 2019 , pp. 10-17 More about this Journal
Abstract
In High Dynamic Range (HDR) image processing, tone mapping is the process to compress an input image into a Low Dynamic Range (LDR) image. In most cases, the reason that detail preservation is prior to take over tone mapping is that the dynamic range is significantly different between input and output images. In the case of iCAM06, details are separated by using a bilateral filter, however, it causes noise amplification at the dim surround region. Thus, we suggest that the detail signal, which is separated from the bilateral filter, is combined with the base signal after an adaptive Kalman filter is applied according to the local standard deviation. We confirmed that the proposed method enhances the HDR images quality by checking the noise reduction in a dim surround region.
Keywords
High Dynamic Range Imaging; iCAM06; Kalman Filter; Detail Composition;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 J. Kuang, G.M. Johnson, and M.D. Fairchild, “iCAM06: A Refined Image Appearance Model for HDR Image Rendering,” Journal of Visual Communication and Image Representation, Vol. 18, No. 5, pp. 406-414, 2007.   DOI
2 A.O. Akyuz and E. Reinhard, “Noise Reduction in High Dynamic Range Imaging,” Journal of Visual Communication and Image Representation, Vol. 18, No. 5, pp. 366-376, 2007.   DOI
3 A.O. Akyuz and E. Reinhard. "Color Appearance in High-Dynamic-Range Imaging," Journal of Electronic Imaging, Vol. 15, No. 3, pp, 033001-1-033001-12, 2006.   DOI
4 M.D. Fairchild, Color Appearance Models, Addison-Wesley, Massachusetts, 2005.
5 R.C. Gonzalez and R.E. Woods, Digital Image Processing, Prentice Hall Press, New Jersey, 2002.
6 L. Meylan and S. Susstrunk, “High Dynamic Range Image Rendering with a Retinex -Based Adaptive Filter,” IEEE Transactions on Image Processing, Vol. 15, No. 9, pp. 2820-2830, 2006.   DOI
7 F. Durand and J. Dorsey, “Fast Bilateral Filtering for the Display of High-Dynamic-Range Images,” Association for Computing Machinery Transactions on Graphics, Vol. 21, No. 3, pp. 257-266, 2002.
8 R.W.G. Hunt, The Reproduction of Color, Fountain Press, England, 1996.
9 E. Reinhard, W. Heidrich, P. Debevec, S. Pattanaik, G. Ward, and K. Myszkowski, et al., High Dyamic Range Imaging: Acquisition, Display and Image-Based Lighting, Morgan Kaufmann Publishers, San Francisco, 2010.
10 P.E. Debevec and J. Malik, "Recovering High Dynamic Range Radiance Maps from Photographs," SIGGRAPH'97 Proceeding of the 24th Annual Conference on Computer Graphics and Interative Techniques, pp. 369-378, 1997.
11 R. Mantiuk, R. Mantiuk, A. Tomaszweska, and W. Heidrich, “Color Correction for Tone Mapping,” Computer Graphics Forum, Vol. 28, No. 2, pp. 193-202, 2009.   DOI
12 S.M. Chae, S.H. Lee, and K.I. Sohng, “Color Correction of the Color Difference in the PT Space for HDR Image Tone Compression using iCAM06,” Journal of Korea Multimedia Society, Vol. 16, No. 3, pp. 281-289, 2013.   DOI
13 G.Y. Lee, S.H. Lee, H.J. Kwon, and K.I. Sohng, “Visual Acuity-Adaptive Detail Enhancement and Shadow Noise Reduction for iCAM06-Based HDR Imaging,” Optical Review, Vol. 22, No. 2, pp. 232-245, 2015.   DOI
14 R.E. Kalman, “A New Approach to Linear Filtering and Prediction Problems,” Journal OF Basic Engineering, Vol. 82, No. 1, pp. 35-45, 1960.   DOI
15 S. Braun and E.A.P. Habets, "Linear Prediction-Based Online Dereverberation and Noise Reduction Using Alternating Kalman Filters," IEEE/ACM Transactions on Audio, Speech, and Language Processing, Vol. 26, Issue 6, pp. 1119-1129, 2018.   DOI