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JBE, vol. 22, no. 6, pp.702-712, November, 2017


Patch based Multi-Exposure Image Fusion using Unsharp Masking and Gamma Transformation

Jihwan Kim, Hyunho Choi, and Jechang Jeong

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In this paper, we propose an unsharp masking algorithm using Laplacian as a weight map for the signal structure and a gamma transformation algorithm using image mean intensity as a weight map for mean intensity. The conventional weight map based on the patch has a disadvantage in that the brightness in the image is shifted to one side in the signal structure and the mean intensity region. So the detailed information is lost. In this paper, we improved the detail using unsharp masking of patch unit and proposed linearly combined the gamma transformed values using the average brightness values of the global and local images. Through the proposed algorithm, the detail information such as edges are preserved and the subjective image quality is improved by adjusting the brightness of the light. Experiment results show that the proposed algorithm show better performance than conventional algorithm.

Keyword: Multi-Exposure Image Fusion, High Dynamic Range, Gamma Transformation, Unsharp Masking, Edge enhancement

[1] S. Jeong, and M. Jeong, “Histogram Equalization using Gamma Transformation,” Journal of Computing Science and Engineering, Vol. 20, No.12, pp. 646-651, 2014.

[2] R. C. Gonzalez, and R. E. Woods. Digital image processing, Pearson, New Jersey, 2010.

[3] S, Hwang, Image processing programming by Visual C++, Hanbit media, 2007.

[4] G. Ramponi, N. Strobel, S. K. Mitra, and T. Yu, "Nonlinear unsharp masking methods for image contrast enhancement", J. Electron. Imag., Vol. 5, pp. 353-366, July 1996.

[5] T. Luft, C. Colditz, and O. Deussen, "Image Enhancement by Unsharp Masking the Depth Buffer," ACM Transactions on Graphics, vol. 25, No. 3, pp. 1206-1213, July 2006.

[6] E. Reinhard, W. Heidrich, P. Debevec, S. Pattanaik, G. Ward, and K. Myszkowski, High Dynamic Range Imaging: Acquisition, Display, and Image-based Lighting, Morgan Kaufmann, 2010.

[7] P. J. Burt, The pyramid as a structure for efficient computation in Multi resolution Image Processing and Analysis, Berlin, Germany: Springer-Verlag, 1984.

[8] K. Ma, K. Zeng, and Z. Wang, “Perceptual quality assessment for multi-exposure image fusion,” IEEE Transactions on Image Processing, Vol. 24, No. 11, pp. 3345-3356, 2015.

[9] S. Li, and X. Kang, "Fast multi-exposure image fusion with median filter and recursive filter," IEEE Trans. Consum. Electron, Vol. 58, No. 2, pp. 626-632, May 2012.

[10] B. Gu, W. Li, J. Wong, M. Zhu, and M. Wang, "Gradient field multi-exposure images fusion for high dynamic range image visualization, "J. Vis. Commun. Image Represent, Vol. 23, No. 4, pp. 604-610, 2012.

[11] S. Raman, and S. Chaudhuri, "Bilateral filter based compositing for variable exposure photography," Proc. Eurographics, pp. 1-4, 2009.

[12] T. Mertens, J. Kautz, and F. Van Reeth, “Exposure fusion: A simple and practical alternative to high dynamic range photography,” Computer Graphics Forum, Vol. 28, No. 1, pp. 161–171, 2009.

[13] P. J. Burt, and R. J. Kolczynski, "Enhanced image capture through fusion," Proc. 4th IEEE ICCV, pp. 173-182, May 1993.

[14] M. Song, D.Tao, C. Chen, J.Luo, and C. Zhang, “Probabilistic exposure fusion,” IEEE Transactions on Image Processing, Vol. 21.1, pp.341-357, 2012.

[15] K. Ma, and Z. Wang, “Multi-exposure image fusion: A patch-wise approach,” IEEE International Conference on Image Processing, pp.1717-1721, 2015.

[16] Y. Liu, and Z. Wang, “Dense sift for ghost-free multi exposure fusion,” Journal of Visual Communication and Image Representation, vol.31, pp. 208–224, 2015. 4


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