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Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815
Bilateral Filtering for Gray and Color Images
Institute of Electrical and Electronics
Engineering
Abstract:-
Bilateral filtering smoothen images while preserving edges, by means of a nonlinear combination of
nearby image values. The method is non-iterative, local, and simple. It combines grey levels or colours
based on both their geometric closeness and their photometric similarity, and prefers near values to
distant values in both domain and range. In contrast with filters that operate on the three bands of a
colour image separately, a bilateral filter can enforce the perceptual metric underlying the CIE-Lab
colour space, and smooth colours and preserve edges in a way that is tuned to human perception. Also,
in contrast with standard filtering, bilateral filtering produces no phantom colours along edges in colour
images, and reduces phantom colours where they appear in the original image.
Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815
(a) Framework of Multi-resolution Bilateral Filter
(b) Framework of Adaptive Bilateral Filter
Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815
A: - Bilateral filter applied on gray level image:
(a) Input gray level image (b) Corresponding bilateral filtered image.
B: - Bilateral filter applied on color image:
(a) Input gray level image (b) Corresponding bilateral filtered image.
Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815
C: - Application of bilateral filters to image abstraction:
(a) Original image
(b) Abstracted image
Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815
Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815
Conclusion:
In this paper we have introduced the concept of bilateral filtering for edge-preserving smoothing. The
generality of bilateral filtering is analogous to that of traditional filtering, which we called domain
filtering in this paper. The explicit enforcement of a photometric distance in the range component of a
bilateral filter makes it possible to process colour images in a perceptually appropriate fashion. The
parameters used for bilateral filtering in our illustrative examples were to some extent arbitrary. This
is however a consequence of the generality of this technique. In fact, just as the parameters of domain
filters depend on image properties and on the intended result, so do those of bilateral filters. Given a
specific application, techniques for the automatic design of filter profiles and parameter values may
be possible.
Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815
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Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815
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2002.June 2008

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Bilateral filtering for gray and color images

  • 1. Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815 Bilateral Filtering for Gray and Color Images Institute of Electrical and Electronics Engineering Abstract:- Bilateral filtering smoothen images while preserving edges, by means of a nonlinear combination of nearby image values. The method is non-iterative, local, and simple. It combines grey levels or colours based on both their geometric closeness and their photometric similarity, and prefers near values to distant values in both domain and range. In contrast with filters that operate on the three bands of a colour image separately, a bilateral filter can enforce the perceptual metric underlying the CIE-Lab colour space, and smooth colours and preserve edges in a way that is tuned to human perception. Also, in contrast with standard filtering, bilateral filtering produces no phantom colours along edges in colour images, and reduces phantom colours where they appear in the original image.
  • 2. Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815 (a) Framework of Multi-resolution Bilateral Filter (b) Framework of Adaptive Bilateral Filter
  • 3. Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815 A: - Bilateral filter applied on gray level image: (a) Input gray level image (b) Corresponding bilateral filtered image. B: - Bilateral filter applied on color image: (a) Input gray level image (b) Corresponding bilateral filtered image.
  • 4. Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815 C: - Application of bilateral filters to image abstraction: (a) Original image
  • 5. (b) Abstracted image Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815
  • 6. Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815 Conclusion: In this paper we have introduced the concept of bilateral filtering for edge-preserving smoothing. The generality of bilateral filtering is analogous to that of traditional filtering, which we called domain filtering in this paper. The explicit enforcement of a photometric distance in the range component of a bilateral filter makes it possible to process colour images in a perceptually appropriate fashion. The parameters used for bilateral filtering in our illustrative examples were to some extent arbitrary. This is however a consequence of the generality of this technique. In fact, just as the parameters of domain filters depend on image properties and on the intended result, so do those of bilateral filters. Given a specific application, techniques for the automatic design of filter profiles and parameter values may be possible.
  • 7. Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710815 References: - [1] T. Boult, R. A. Melter, F. Skorina, and I. Stojmenovic. G-neighbors. Proc. SPIE Conf. on Vision Geometry II, 96–109, 1993. [2] R. T. Chin and C. L. Yeh. Quantitative evaluation of some edgepreserving noise-smoothing techniques. CVGIP, 23:67–91, 1983. [3] L. S. Davis and A. Rosenfeld. Noise cleaning by iterated local averaging. IEEE Trans., SMC-8:705–710, 1978. [4] R.E.Graham. Snow-removal—a noise-stripping process for picture signals. IRE Trans., IT-8:129– 144, 1961. [5] N. Himayat and S.A. Kassam. Approximate performance analysis of edge preserving filters. IEEE Trans., SP-41(9):2764–77, 1993. [6] T. S. Huang, G. J. Yang, and G. Y. Tang. A fast two-dimensional median filtering algorithm. IEEE Trans., ASSP- 27(1):13–18, 1979. [7] J. S. Lee. Digital image enhancement and noise filtering by use of local statistics. IEEE Trans., PAMI-2(2):165– 168, 1980. [8] M. Nagao and T. Matsuyama. Edge preserving smoothing. CGIP, 9:394–407, 1979. [9] P.M.Narendra. Aseparable median filter for image noise smoothing. IEEE Trans., PAMI-3(1):20–29, 1981. [10] K. J. Overton and T. E. Weymouth. A noise reducing preprocessing algorithm. In Proc. IEEE Computer Science Conf. on Pattern Recognition and Image Processing, 498–507, 1979. [11] Athanasios Papoulis. Probability, random variables, and stochastic processes. McGraw-Hill, New York, 1991. [12] P. Perona and J. Malik. Scale-space and edge detection using anisotropic diffusion. IEEE Trans., PAMI- 2(7):629–639, 1990. [13] G. Ramponi. A rational edge-preserving smoother. In Proc. Int’l Conf. on Image Processing, 1:151–154, 1995. [14] G. Sapiro and D. L. Ringach. Anisotropic diffusion of color images. In Proc. SPIE, 2657:471–382, 1996. [15] D. C. C. Wang, A. H. Vagnucci, and C. C. Li. A gradient inverse weighted smoothing scheme and the evaluation of its performance. CVGIP, 15:167–181, 1981. [16] G.Wyszecki andW. S. Styles. Color Science: Concepts and Methods, Quantitative Data and Formulae. Wiley, New York, NY, 1982. [17] L. Yin, R. Yang, M. Gabbouj, and Y. Neuvo. Weighted median filters: a tutorial. IEEE Trans., CAS-II-43(3): 155–192, 1996. Additional References: - 1. C. Tomasi and R. Manduchi, “Bilateral filtering for gray and color images,” Proc. Int. Conf. Computer Vision, 1998, pp. 839–846.
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