Abstract
Laplacian Pyramid Blending is a commonly used method for several seamless image blending tasks. While the method works well for images with comparable intensity levels, it is often unable to produce artifact free images for applications which handle images with large intensity variation such as exposure fusion. This paper proposes a spatially varying Laplacian Pyramid Blending to blend images with large intensity differences. The proposed method dynamically alters the blending levels during the final stage of Pyramid Reconstruction based on the amount of local intensity variation. The proposed algorithm out performs state-of-the-art methods for image blending both qualitatively as well as quantitatively on publicly available High Dynamic Range (HDR) imaging dataset. Qualitative improvements are demonstrated in terms of details, halos and dark halos. For quantitative comparison, the no-reference perceptual metric MEF-SSIM was used.
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References
Burt, P., Adelson, E.: The Laplacian pyramid as a compact image code. IEEE Trans. Commun. 31, 532–540 (1983)
Mertens, T., Kautz, J., Van Reeth, F.: Exposure fusion: a simple and practical alternative to high dynamic range photography. Comput. Graph Forum 28, 161–171 (2009)
Debevec, P.E., Malik, J.: Recovering high dynamic range radiance maps from photographs. In: ACM SIGGRAPH 2008 Classes, p. 31. ACM (2008)
Robertson, M.A., Borman, S., Stevenson, R.L.: Dynamic range improvement through multiple exposures. In: Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348), vol. 3, pp. 159–163. IEEE (1999)
Tursun, O.T., Akyüz, A.O., Erdem, A., Erdem, E.: The state of the art in HDR deghosting: a survey and evaluation. Comput. Graph Forum 34, 683–707 (2015)
Shen, J., Zhao, Y., Yan, S., Li, X., et al.: Exposure fusion using boosting Laplacian pyramid. IEEE Trans. Cybern. 44, 1579–1590 (2014)
Li, Z., Zheng, J., Zhu, Z., Yao, W., Wu, S.: Weighted guided image filtering. IEEE Trans. Image Process. 24, 120–129 (2014)
Gu, B., Li, W., Wong, J., Zhu, M., Wang, M.: Gradient field multi-exposure images fusion for high dynamic range image visualization. J. Vis. Commun. Image Represent. 23, 604–610 (2012)
Hasinoff, S.W., et al.: Burst photography for high dynamic range and low-light imaging on mobile cameras. ACM Trans. Graphics (TOG) 35, 192 (2016)
Ma, K., Zeng, K., Wang, Z.: Perceptual quality assessment for multi-exposure image fusion. IEEE Trans. Image Process. 24, 3345–3356 (2015)
Raman, S., Chaudhuri, S.: Bilateral filter based compositing for variable exposure photography. In: Eurographics (Short Papers), pp. 1–4 (2009)
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P., et al.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13, 600–612 (2004)
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Biswas, A., Green Rosh, K.S., Lomte, S.D. (2020). Spatially Variant Laplacian Pyramids for Multi-frame Exposure Fusion. In: Nain, N., Vipparthi, S., Raman, B. (eds) Computer Vision and Image Processing. CVIP 2019. Communications in Computer and Information Science, vol 1147. Springer, Singapore. https://doi.org/10.1007/978-981-15-4015-8_7
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DOI: https://doi.org/10.1007/978-981-15-4015-8_7
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