Abstract
In the paper, a method of edge-preserving processing of color images, called LPMPR (Low-Pass filter with Morphologically Processed Residuals), is proposed. It combines linear low-pass filtering with non-linear techniques, that allow for selecting meaningful regions of the image, where edges should be preserved. The selection of those regions is based on morphological processing of the linear filter residuals and aims to find meaningful regions characterized by edges of high amplitude and appropriate size. To find them, two methods of morphological image processing are used: reconstruction operator and area opening. The meaningful reconstructed regions are finally combined with the low-pass filtering result to recover the edges’ original shape. Besides, the method allows for controlling the contrast of the output image. The processing result depends on four parameters, the choice of which allows for adjusting the processed image to particular requirements. Results of experiments, showing example filtering results, are also presented in the paper.
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Notes
- 1.
The MATLAB code of the proposed filtering method is available at https://www.mathworks.com/matlabcentral/fileexchange/77581-lpmpr-image-filter.
References
Barash, D.: Fundamental relationship between bilateral filtering, adaptive smoothing, and the nonlinear diffusion equation. IEEE Trans. Pattern Anal. Mach. Intell. 24(6), 844–847 (2002)
Durand, F., Dorsey, J.: Fast bilateral filtering for the display of high-dynamic-range images. ACM Trans. Graph. 21(3), 257–266 (2002)
Grazzini, J., Soille, P.: Edge-preserving smoothing using a similarity measure in adaptive geodesic neighbourhoods. Pattern Recogn. 42(10), 2306–2316 (2009). Selected papers from the 14th IAPR International Conference on Discrete Geometry for Computer Imagery 2008
He, K., Sun, J., Tang, X.: Guided image filtering. IEEE Trans. Pattern Anal. Mach. Intell. 35(6), 1397–1409 (2013)
Hong, V., Palus, H., Paulus, D.: Edge preserving filters on color images. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2004. LNCS, vol. 3039, pp. 34–40. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-25944-2_5
Iwanowski, M.: Morphological processing of Gaussian residuals for edge-preserving smoothing. In: Angulo, J., Velasco-Forero, S., Meyer, F. (eds.) ISMM 2017. LNCS, vol. 10225, pp. 331–341. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-57240-6_27
Kuwahara, M., Hachimura, K., Eiho, S., Kinoshita, M.: Processing of RI-angiocardiographic images. In: Preston, K., Onoe, M. (eds.) Digital Processing of Biomedical Images, pp. 187–202. Springer, Boston (1976). https://doi.org/10.1007/978-1-4684-0769-3_13
Nagao, M., Matsuyama, T.: Edge preserving smoothing. Comput. Graph. Image Process. 9(4), 394–407 (1979)
Perona, P., Malik, J.: Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Anal. Mach. Intell. 12(7), 629–639 (1990)
Saint-Marc, P., Chen, J., Medioni, G.: Adaptive smoothing: a general tool for early vision. IEEE Trans. Pattern Anal. Mach. Intell. 13(6), 514–529 (1991)
Soille, P.: Morphological Image Analysis: Principles and Applications. Springer, Berlin (2004). https://doi.org/10.1007/978-3-662-05088-0
Tomasi, C., Manduchi, R.: Bilateral filtering for gray and color images. In: Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271), pp. 839–846, January 1998
Wheeler, M.D., Ikeuchi, K.: Iterative smoothed residuals: a low-pass filter for smoothing with controlled shrinkage. IEEE Trans. Pattern Anal. Mach. Intell. 18(3), 334–337 (1996)
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Iwanowski, M. (2020). Edge-Aware Color Image Manipulation by Combination of Low-Pass Linear Filter and Morphological Processing of Its Residuals. In: Chmielewski, L.J., Kozera, R., Orłowski, A. (eds) Computer Vision and Graphics. ICCVG 2020. Lecture Notes in Computer Science(), vol 12334. Springer, Cham. https://doi.org/10.1007/978-3-030-59006-2_6
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