##plugins.themes.academic_pro.article.main##
Abstract
Edge detection is mainly used in image processing, and is used for feature selection and feature extraction. Edge preservation is important in filtering design to avoid the halo artifacts. Edge preserving decomposition of an image can be achieved using a Local Edge Preserving (LEP) filter. This technique is suitable for High Dynamic Range (HDR) images. Here, multi scale decomposition process is used, in which the image is divided into base layer and detail layer. The output of LEP provides better visual quality to the images. The problem of LEP filter is that it is not capable of eliminating the noise at the output completely and the smoothening performance of the LEP filter is poor compared with the previously established filters. Therefore a median filter is used as the preprocessor. The median filter has the ability to preserve the edges, and the capability to remove the noise present at the input. Thus, the LEP filter performance gets improved by using the median filter as the preprocessor.
Index Terms-- High dynamic range image; local edge preserving filter; LEP-median architecture; multi scale decomposition; tone mapping; quality analysis.##plugins.themes.academic_pro.article.details##
References
2. J. M. DiCarlo and B. A. Wandell, “Rendering high dynamic range imagesâ€, Proc. SPIE, vol. 3965, pp. 392–401, May 2000.
3. R. Kimmel, M. Elad, D. Shaked, R. Keshet, and I. Sobel, “A variational framework for retinexâ€, Int. J. Comput. Vis., vol. 52, no. 1, pp. 7–23, 2003.
4. E. H. Land and J. J. McCann, “Lightness and retinex theoryâ€, J. Opt. Soc. Amer., vol. 61, no. 1, pp. 1–11, Jan. 1971.
5. M. Elad, “Retinex by two bilateral filtersâ€, in Proc. 5th Int. Conf. Scale Space PDE Methods Comput. Vis., vol. 3459, pp. 217–229, Apr.2005.
6. Z. Farbman, R. Fattal, D. Lischinski, and R. Szeliski, “Edge-preserving decompositions for multi-scale tone and detail manipulationâ€, ACM Trans. Graph., vol. 27, no. 3, pp. 1–10, Aug. 2008.
7. K. Subr, C. Soler, and F. Durand, “Edge-preserving multiscale image decomposition based on local extremaâ€, ACM Trans. Graph., vol. 28, no. 5, pp. 147–155, Dec. 2009.
8. G. Guarnieri, S. Marsi, and G. Ramponi, “High dynamic range image display with halo and clipping preventionâ€, IEEE Trans. Image Process., vol. 20, no. 5, pp. 1351–1362, May 2011.
9. R. Fattal, D. Lischinski, and M. Werman, “Gradient domain high dynamic range compressionâ€, ACM Trans. Graph., vol. 21, no. 3, pp. 249–256, Jul. 2002.
10. F. Drago, W. L. Martens, K. Myszkowski, and N. Chiba, “Design of a tone mapping operator for high dynamic range images based upon psychophysical evaluation and preference mappingâ€, Proc. SPIE, vol.5007, pp. 321–331, Jun. 2003.
11. P. E. Debevec and J. Malik, “Recovering high dynamic range radiance maps from photographsâ€, in Proc. SIGGRAPH, vol. 31, pp. 369–378, Aug. 1997.
12. S. Battiato, A. Castorina, and M. Mancuso, “High dynamic range imaging for digital still camera: An overviewâ€, J. Electron. Imag., vol. 12, no. 3, pp. 459–469, July 2003.
13. Z. Rahman, D. J. Jobson, and G. A. Woodell, “Retinex processing for automatic image enhancementâ€, J. Electron. Imag., vol. 13, no. 1, pp.100–110, Jan.2004.
14. D. J. Jobson, Z. Rahman, and G. A. Woodell, “Properties and performance of a center/surround retinexâ€, IEEE Trans. Image Process., vol. 6, no. 3, pp. 451–462, Mar. 1997.
15. Hojatollah Yeganeh,and Zhou Wang, “Objective Quality Assessment of Tone-Mapped Imagesâ€, IEEE Trans. Image Process., vol. 22, no. 2, pp. 657-667, Feb. 2013.