Abstract
Decomposition of an image into its cartoon part and texture part has been an interesting area of research. It is an important pre-processing step in many computer vision and image processing techniques such as image segmentation, pattern matching, object recognition, tone mapping as both cartoon and texture parts contain two different kinds of information. Significant work is already available in the literature. At the time of decomposition of an input image into its cartoon and texture part, we required texture-smoothing along with edge-preservation. Most of the approaches available in the literature establish a trade-off between the edge preservation and the texture-smoothing. This common drawback of the existing approaches motivates us to design a new image decomposition method by which we can achieve texture-smoothing without having any loss of edge information in cartoon part. To achieve this aim we introduce a new approach based on Joint bilateral filter and DCT (Discrete cosine transform). We show experimental results on several images to show the effectiveness of our method and comparison with some state-of-the-art methods.
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References
Ahmed N, Natarajan T, Rao KR (1974) Discrete cosine transform. IEEE Trans Comput 100(1):90–93
Aujol J-F, Aubert G, Blanc-Féraud L, Chambolle A (2003) Image decomposition application to sar images. In: Scale space methods in computer vision. Springer, pp 297–312
Aujol J-F, Gilboa G, Chan T, Osher S (2006) cois Structure-texture image decompositionmodeling, algorithms, and parameter selection. Int J Comput Vis 67(1):111–136
Buades A, Le TM, Morel J M, Vese LA (2010) Fast cartoon+ texture image filters. IEEE Trans Image Process 19(8):1978–1986
Canny J (1986) A computational approach to edge detection. IEEE Trans Pattern Anal Mach Intell 6:679–698
Chambolle A, Thomas P (2011) A first-order primal-dual algorithm for convex problems with applications to imaging. J Math Imaging Vis 4(1):120–145
Farbman Z, Fattal R, Lischinski D, Szeliski R (2008) Edge-preserving decompositions for multi-scale tone and detail manipulation. ACM Trans Graph (TOG) 27(3):artical 67. ACM
Fattal R (2009) Edge-avoiding wavelets and their applications. ACM Trans Graph (TOG) 28(3):artical 22. ACM
Feng L, Wu Z, Luo P, Ma T (2013) Computational geometry-based scale space for edge-preserving multiscale image decomposition. J Electron Imaging 22 (1):013027–013027
Haralick RM, Shanmugam KD (1973) Its’ hak. textural features for image classification. IEEE Trans Syst Man Cybern 6:610–621
Jiang X, Yao H, Zhao S (2013) Edge-respecting image smoothing via extrema interpolation. In: Advances in multimedia information processing–pcm 2013, pp 190–199
Karacan L, Erdem E, Erdem A (2013) Structure-preserving image smoothing via region covariances. ACM Trans Graph (TOG) 32(6):artical 176
Le Guen V (2014) Cartoon + texture image decomposition by the TV-l1 model. Image Process Line 4:204–219
Leng L, Li M, Zhang JS (2010) Histogram equalization algorithm with local adaptive enhancement based on edge details. Microelectron Comput 27:38–41
Leng L, Zhang J, Xu J, Khan MK, Alghathbar K (2010) Dynamic weighted discrimination power analysis in dct domain for face and palmprint recognition. In: 2010 international conference on information and communication technology convergence (ICTC). Jeju, pp 467–471. https://doi.org/10.1109/ICTC.2010.5674791
Lu L, Zhang J, Xu J, Khan MK, Alghathbar K (2010) Dynamic weighted discrimination power analysis: A novel approach for face and palmprint recognition in dct domain. Int J Phys Sci 5(17):2543–2554
Meyer Y (2001) Oscillating patterns in image processing and nonlinear evolution equations: the fifteenth dean Jacqueline B. Lewis memorial lectures, vol 22. American Mathematical Society
Mohanaiah P, Sathyanarayana P, GuruKumar L. (2013) Image texture feature extraction using glcm approach. Int J Sci Res Publ 3(5):122
Ono S, Miyata T, Yamada I (2014) Cartoon-texture image decomposition using blockwise low-rank texture characterization. IEEE Trans IEEE Image Process 23 (3):1128–1142
Paris S, Durand F (2009) A fast approximation of the bilateral filter using a signal processing approach. Int J Comput Vis 81(1):24–52
Petschnigg G, Szeliski R, Agrawala M, Cohen M, Hoppe H, Toyama K (2004) Digital photography with flash and no-flash image pairs. ACM Trans Graph (TOG) 23(3):664–672
Su Z, Luo X, Artusi A (2013) A novel image decomposition approach and its applications. Vis Comput 29(10):1011–1023
Subr K, Soler C, Durand F (2009) Edge-preserving multiscale image decomposition based on local extrema. ACM Trans Graph (TOG) 28(5):artical 147
Tomasi C, Manduchi R (1998) Bilateral filtering for gray and color images. In: 1998. Sixth international conference on computer vision. IEEE, pp 839–846
Vese LA, Osher SJ (2003) Modeling textures with total variation minimization and oscillating patterns in image processing. J Sci Comput 19(1):553–572
Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13 (4):600–612
Xu L, Lu C, Xu Y, Jia J (2011) Image smoothing via l 0 gradient minimization. ACM Trans Graph (TOG) 30(6):artical 174
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We would like to forward our thanks to anonymous referees, who spend their precious time in reviewing our work. We would like to acknowledge their contribution due to which there was significant improvement in the article. Also, we are grateful to the editor associated with this paper for their cooperation.
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Gupta, B., Singh, A. A new computational approach for edge-preserving image decomposition. Multimed Tools Appl 77, 19527–19546 (2018). https://doi.org/10.1007/s11042-017-5401-7
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DOI: https://doi.org/10.1007/s11042-017-5401-7