×

Relative reductive structure-aware regression filter. (English) Zbl 1372.94241

Summary: Structure-aware image smoothing is a challenging and significant technique to remedy the limitation of current edge-preserving smoothing filters for extracting the prominent structures. To improve the technique, we propose a novel structure-aware filter via bilateral kernel regression with a variational structure-kernel descriptor. First, the relative reductive texture decomposition is applied to construct the structure-kernel descriptor. Then, the descriptor is incorporated into the bilateral kernel regression to achieve an expected structure preservation output. Algorithmically, a close-form numerically iterative solver is exploited to achieve the efficient and effective implementation. At last, some experimental self-evaluations and visual applications are presented to demonstrate that our method leads to better performance than the state-of-the-art solutions.

MSC:

94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
62H35 Image analysis in multivariate analysis
68U10 Computing methodologies for image processing
Full Text: DOI

References:

[2] Farbman, Z.; Fattal, R.; Lischinski, D.; Szeliski, R., Edge-preserving decompositions for multi-scale tone and detail manipulation, ACM Trans. Graph., 27, 3, 67-76 (2008)
[3] Xu, L.; Lu, C.; Xu, Y.; Jia, J., Image smoothing via l0 gradient minimization, ACM Trans. Graph., 30, 6, 174:1-174:12 (2011)
[4] Bhat, P.; Zitnick, C.; Cohen, M.; Curless, B., Gradientshop: A gradient-domain optimization framework for image and video filtering, ACM Trans. Graph., 29, 2, 1-14 (2010)
[6] Badri, H.; Yahia, H.; ABOUTAJDINE, D., Fast edge-aware processing via first order proximal approximation, IEEE Trans. Vis. Comput. Graphics, 21, 6, 1 (2015)
[7] He, K.; Sun, J.; Tang, X., Guided image filtering, IEEE Trans. Pattern Anal. Mach. Intell., 35, 6, 1397-1409 (2013)
[8] Qiu, T.; Wang, A.; Yu, N.; Song, A., LLSURE: Local linear sure-based edge-preserving image filtering, IEEE Trans. Image Process., 22, 1, 80-90 (2013) · Zbl 1373.94336
[9] Subr, K.; Soler, C.; Durand, F., Edge-preserving multiscale image decomposition based on local extrema, ACM Trans. Graph., 28, 5, 147:1-147:9 (2009)
[10] Yu, Z.; Hua, H.; Lei, Z., Efficient structure-aware image smoothingby local extrema on space-filling curve, IEEE Trans. Vis. Comput. Graphics, 20, 9, 1253-1265 (2014)
[11] Su, Z.; Luo, X.; Deng, Z.; Liang, Y.; Ji, Z., Edge-preserving texture suppression filter based on joint filtering schemes, IEEE Trans. Multimedia, 15, 3, 535-548 (2013)
[12] Karacan, L.; Erdem, E.; Erdem, A., Structure-preserving image smoothing via region covariances, ACM Trans. Graph., 32, 6, 176 (2013)
[13] Bao, L.; Song, Y.; Yang, Q.; Yuan, H.; Wang, G., Tree filtering: Efficient structure-preserving smoothing with a minimum spanning tree, IEEE Trans. Image Process., 23, 2, 555-569 (2014) · Zbl 1374.94031
[14] Vese, L. A.; Osher, S. J., Image denoising and decomposition with total variation minimization and oscillatory functions, J. Math. Imaging Vision, 20, 1-2, 7-18 (2004) · Zbl 1366.94072
[15] Aujol, J. F.; Gilboa, G.; Chan, T.; Osher, S., Structure-texture image decomposition-modeling, algorithms and parameter selection, Int. J. Comput. Vis., 67, 1, 111-136 (2006) · Zbl 1287.94011
[16] Buades, A.; Le, T. M.; Morel, J. M.; Vese, L. A., Fast cartoon + texture image filters, IEEE Trans. Image Process., 19, 8, 1978-1986 (2010) · Zbl 1371.94064
[17] Xu, L.; Yan, Q.; Xia, Y.; Jia, J., Structure extraction from texture via relative total variation, ACM Trans. Graph., 31, 6, 139:1-139:10 (2012)
[18] Cho, H.; Lee, H.; Kang, H.; Lee, S., Bilateral texture filtering, ACM Trans. Graph., 33, 4, 128 (2014)
[20] Paris, S.; Durand, F., A fast approximation of the bilateral filter using a signal processing approach, Int. J. Comput. Vis., 81, 1, 24-52 (2009)
[21] Takeda, H.; Farsiu, S.; Milanfar, P., Kernel regression for image processing and reconstruction, IEEE Trans. Image Process., 16, 2, 349-366 (2007)
[22] Milanfar, P., A tour of modern image filtering: New insights and methods, both practical and theoretical, IEEE Signal Process. Mag., 30, 1, 106-128 (2013)
[24] Zhang, Q.; Shen, X.; Xu, L.; Jia, J., Rolling guidance filter, (Computer Vision C ECCV (2014), Springer International Publishing), 815-830
[25] Xu, L.; Yan, Q.; Xia, Y.; Jia, J., Structure extraction from texture via relative total variation, ACM Trans. Graph., 31, 6, 139 (2012)
[26] Wang, Z.; Bovik, A.; Sheikh, H.; Simoncelli, E., Image quality assessment: From error visibility to structural similarity, IEEE Trans. Image Process., 13, 4, 600-612 (2004)
[27] Gonzalez, R.; Woods, R., Digital Image Processing (2008), Prentice Hall: Prentice Hall Upper Saddle River
[28] Luo, X.; Zhao, Z.; Su, Z.; Liang, Y., Multiple-cue saliency measurement and optimized image composition for image retargeting, J. Comput. Appl. Math., 236, 704-713 (2011) · Zbl 1236.94022
[29] Durand, F.; Dorsey, J., Fast bilateral filtering for the display of high-dynamic-range images, ACM Trans. Graph., 21, 3, 257-266 (2002)
[30] Winnemöller, H.; Olsen, S. C.; Gooch, B., Real-time video abstraction, ACM Trans. Graph., 25, 3, 1221-1226 (2006)
[31] Achanta, R.; Shaji, A.; Smith, K.; Lucchi, A.; Fua, P.; Susstrunk, S., Slic superpixels compared to state-of-the-art superpixel methods, IEEE Trans. Pattern Anal. Mach. Intell., 34, 11, 2274-2282 (2012)
[32] Aubry, M.; Paris, S.; Hasinoff, S.; Kautz, J.; Durand, F., Fast local Laplacian filters: Theory and applications, ACM Trans. Graph., 33, 5, 167 (2014)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.