Skip to main content
Erschienen in: International Journal of Computer Vision 11/2018

23.04.2018

Joint Contour Filtering

verfasst von: Xing Wei, Qingxiong Yang, Yihong Gong

Erschienen in: International Journal of Computer Vision | Ausgabe 11/2018

Einloggen

Aktivieren Sie unsere intelligente Suche um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Edge/structure-preserving operations for images aim to smooth images without blurring the edges/structures. Many exemplary edge-preserving filtering methods have recently been proposed to reduce the computational complexity and/or separate structures of different scales. They normally adopt a user-selected scale measurement to control the detail smoothing. However, natural photos contain objects of different sizes, which cannot be described by a single scale measurement. On the other hand, contour analysis is closely related to edge-preserving filtering, and significant progress has recently been achieved. Nevertheless, the majority of state-of-the-art filtering techniques have ignored the successes in this area. Inspired by the fact that learning-based edge detectors significantly outperform traditional manually-designed detectors, this paper proposes a learning-based edge-preserving filtering technique. It synergistically combines the differential operations in edge-preserving filters with the effectiveness of the recent edge detectors for scale-aware filtering. Unlike previous filtering methods, the proposed filters can efficiently extract subjectively meaningful structures from natural scenes containing multiple-scale objects.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Fußnoten
1
The structure-preserving filtering can be considered as a special design of edge-preserving filtering to deal with its limitation in handling textures. In most cases, this paper adopts the phrase “edge-preserving” for a broader concept.
 
2
The implementations with the default parameters published by the authors were employed.
 
3
Experiments conducted in this study use two iterations, except for the large-scale texture removal task in Sect. 4.1, which requires more iterations to smooth large-scale highly-textured images.
 
4
Please note that when a spatial parameter is a fractional number, it represents the percentage of width/height of the image.
 
Literatur
Zurück zum Zitat Adams, A., Baek, J., & Davis, A. (2010). Fast high-dimensional filtering using the permutohedral lattice. CGF, 29(2), 753–762. Adams, A., Baek, J., & Davis, A. (2010). Fast high-dimensional filtering using the permutohedral lattice. CGF, 29(2), 753–762.
Zurück zum Zitat Adams, A., Gelfand, N., Dolson, J., & Levoy, M. (2009). Gaussian kd-trees for fast high-dimensional filtering. ACM TOG (SIGGRAPH), 28, 21:1–21:12. Adams, A., Gelfand, N., Dolson, J., & Levoy, M. (2009). Gaussian kd-trees for fast high-dimensional filtering. ACM TOG (SIGGRAPH), 28, 21:1–21:12.
Zurück zum Zitat An, X., & Pellacini, F. (2008). Appprop: All-pairs appearance-space edit propagation. ACM TOG (SIGGRAPH Asia), 27(3), 40:1–40:9. An, X., & Pellacini, F. (2008). Appprop: All-pairs appearance-space edit propagation. ACM TOG (SIGGRAPH Asia), 27(3), 40:1–40:9.
Zurück zum Zitat Arbelaez, P., Maire, M., Fowlkes, C., & Malik, J. (2011). Contour detectionand hierarchical image segmentation. IEEE TPAMI, 33, 898–916.CrossRef Arbelaez, P., Maire, M., Fowlkes, C., & Malik, J. (2011). Contour detectionand hierarchical image segmentation. IEEE TPAMI, 33, 898–916.CrossRef
Zurück zum Zitat Arbeláez, P., Pont-Tuset, J., Barron, J., Marques, F., & Malik, J. (2014). Multiscale combinatorial grouping. In CVPR. Arbeláez, P., Pont-Tuset, J., Barron, J., Marques, F., & Malik, J. (2014). Multiscale combinatorial grouping. In CVPR.
Zurück zum Zitat Arnheim, R. (1956). Art and visual perception: A psychology of the creative eye. Berkeley: University of California Press. Arnheim, R. (1956). Art and visual perception: A psychology of the creative eye. Berkeley: University of California Press.
Zurück zum Zitat Aujol, J., Gilboa, G., Chan, T., & Osher, S. (2006). Structure–texture image decomposition-modeling, algorithms, and parameter selection. IJCV, 67(1), 111–136.CrossRefMATH Aujol, J., Gilboa, G., Chan, T., & Osher, S. (2006). Structure–texture image decomposition-modeling, algorithms, and parameter selection. IJCV, 67(1), 111–136.CrossRefMATH
Zurück zum Zitat Avidan, S., & Shamir, A. (2007). Seam carving for content-aware image resizing. ACM TOG (SIGGRAPH), 26(3), 10.CrossRef Avidan, S., & Shamir, A. (2007). Seam carving for content-aware image resizing. ACM TOG (SIGGRAPH), 26(3), 10.CrossRef
Zurück zum Zitat Bertasius, G., Shi, J., & Torresani, L. (2015a). Deepedge: A multi-scale bifurcated deep network for top-down contour detection. In CVPR. Bertasius, G., Shi, J., & Torresani, L. (2015a). Deepedge: A multi-scale bifurcated deep network for top-down contour detection. In CVPR.
Zurück zum Zitat Bertasius, G., Shi, J., & Torresani, L. (2015b). High-for-low and low-for-high: Efficient boundary detection from deep object features and its applications to high-level vision. In ICCV. Bertasius, G., Shi, J., & Torresani, L. (2015b). High-for-low and low-for-high: Efficient boundary detection from deep object features and its applications to high-level vision. In ICCV.
Zurück zum Zitat Bousseau, A., Paris, S., & Durand, F. (2009). User-assisted intrinsic images. ACM TOG (SIGGRAPH Asia), 28, 130:1–130:10. Bousseau, A., Paris, S., & Durand, F. (2009). User-assisted intrinsic images. ACM TOG (SIGGRAPH Asia), 28, 130:1–130:10.
Zurück zum Zitat Boyadzhiev, I., Bala, K., Paris, S., & Durand, F. (2012). User-guided white balance for mixed lighting conditions. ACM TOG (SIGGRAPH Asia), 31(6), 200:1–200:10. Boyadzhiev, I., Bala, K., Paris, S., & Durand, F. (2012). User-guided white balance for mixed lighting conditions. ACM TOG (SIGGRAPH Asia), 31(6), 200:1–200:10.
Zurück zum Zitat Buades, A., & Lisani, J. L. (2016). Directional filters for color cartoon+texture image and video decomposition. Journal of Mathematical Imaging and Vision, 55(1), 125–135.MathSciNetCrossRef Buades, A., & Lisani, J. L. (2016). Directional filters for color cartoon+texture image and video decomposition. Journal of Mathematical Imaging and Vision, 55(1), 125–135.MathSciNetCrossRef
Zurück zum Zitat Canny, J. (1986). A computational approach to edge detection. In IEEE TPAMI. Canny, J. (1986). A computational approach to edge detection. In IEEE TPAMI.
Zurück zum Zitat Catanzaro, B., Su, B. Y., Sundaram, N., Lee, Y., Murphy, M., & Keutzer, K. (2009). Efficient, high-quality image contour detection. In ICCV. Catanzaro, B., Su, B. Y., Sundaram, N., Lee, Y., Murphy, M., & Keutzer, K. (2009). Efficient, high-quality image contour detection. In ICCV.
Zurück zum Zitat Chambolle, A., & Darbon, J. (2009). On total variation minimization and surface evolution using parametric maximum flows. IJCV, 84(3), 288–307.CrossRefMATH Chambolle, A., & Darbon, J. (2009). On total variation minimization and surface evolution using parametric maximum flows. IJCV, 84(3), 288–307.CrossRefMATH
Zurück zum Zitat Chen, J., Paris, S., & Durand, F. (2007). Real-time edge-aware image processing with the bilateral grid. ACM TOG (SIGGRAPH), 26(3), 103.CrossRef Chen, J., Paris, S., & Durand, F. (2007). Real-time edge-aware image processing with the bilateral grid. ACM TOG (SIGGRAPH), 26(3), 103.CrossRef
Zurück zum Zitat Cho, H., Lee, H., Kang, H., & Lee, S. (2014). Bilateral texture filtering. ACM TOG (SIGGRAPH), 33(4), 128:1–128:8. Cho, H., Lee, H., Kang, H., & Lee, S. (2014). Bilateral texture filtering. ACM TOG (SIGGRAPH), 33(4), 128:1–128:8.
Zurück zum Zitat Criminisi, A., Sharp, T., Rother, C., & Perez, P. (2010). Geodesic image and video editing. ACM TOG, 29(5), 134.CrossRef Criminisi, A., Sharp, T., Rother, C., & Perez, P. (2010). Geodesic image and video editing. ACM TOG, 29(5), 134.CrossRef
Zurück zum Zitat Dani, A. L., Lischinski, D., & Weiss, Y. (2004). Colorization using optimization. ACM TOG (SIGGRAPH), 23, 689–694.CrossRef Dani, A. L., Lischinski, D., & Weiss, Y. (2004). Colorization using optimization. ACM TOG (SIGGRAPH), 23, 689–694.CrossRef
Zurück zum Zitat Dollár, P., Tu, Z., & Belongie, S. (2006). Supervised learning of edges and object boundaries. In CVPR. Dollár, P., Tu, Z., & Belongie, S. (2006). Supervised learning of edges and object boundaries. In CVPR.
Zurück zum Zitat Dollár, P., & Zitnick, C. L. (2013). Structured forests for fast edge detection. In ICCV. Dollár, P., & Zitnick, C. L. (2013). Structured forests for fast edge detection. In ICCV.
Zurück zum Zitat Dollár, P., & Zitnick, C. L. (2015). Fast edge detection using structured forests. IEEE TPAMI. Dollár, P., & Zitnick, C. L. (2015). Fast edge detection using structured forests. IEEE TPAMI.
Zurück zum Zitat Donoho, D., Chui, C., Coifman, R. R., & Lafon, S. (2006). Diffusion maps. Applied and Computational Harmonic Analysis, 21(1), 5–30.MathSciNetCrossRefMATH Donoho, D., Chui, C., Coifman, R. R., & Lafon, S. (2006). Diffusion maps. Applied and Computational Harmonic Analysis, 21(1), 5–30.MathSciNetCrossRefMATH
Zurück zum Zitat Duda, R. O., & Hart, P. E. (1973). Pattern classification and scene analysis. New York: Wiley.MATH Duda, R. O., & Hart, P. E. (1973). Pattern classification and scene analysis. New York: Wiley.MATH
Zurück zum Zitat Durand, F., & Dorsey, J. (2002). Fast bilateral filtering for the display of high-dynamic-range images. ACM TOG (SIGGRAPH), 21(3), 257–266. Durand, F., & Dorsey, J. (2002). Fast bilateral filtering for the display of high-dynamic-range images. ACM TOG (SIGGRAPH), 21(3), 257–266.
Zurück zum Zitat Eisemann, E., & Durand, F. (2004). Flash photography enhancement via intrinsic relighting. ACM TOG (SIGGRAPH), 23(3), 673–678.CrossRef Eisemann, E., & Durand, F. (2004). Flash photography enhancement via intrinsic relighting. ACM TOG (SIGGRAPH), 23(3), 673–678.CrossRef
Zurück zum Zitat Farbman, Z., Fattal, R., & Lischinski, D. (2010). Diffusion maps for edge-aware image editing. ACM TOG (SIGGRAPH Asia), 29(6), 145:1–145:10. Farbman, Z., Fattal, R., & Lischinski, D. (2010). Diffusion maps for edge-aware image editing. ACM TOG (SIGGRAPH Asia), 29(6), 145:1–145:10.
Zurück zum Zitat Farbman, Z., Fattal, R., Lischinski, D., & Szeliski, R. (2008). Edge-preserving decompositions for multi-scale tone and detail manipulation. ACM TOG (SIGGRAPH), 27(3), 67. Farbman, Z., Fattal, R., Lischinski, D., & Szeliski, R. (2008). Edge-preserving decompositions for multi-scale tone and detail manipulation. ACM TOG (SIGGRAPH), 27(3), 67.
Zurück zum Zitat Fattal, R. (2009). Edge-avoiding wavelets and their applications. ACM TOG (SIGGRAPH), 28(3), 1–10.CrossRef Fattal, R. (2009). Edge-avoiding wavelets and their applications. ACM TOG (SIGGRAPH), 28(3), 1–10.CrossRef
Zurück zum Zitat Gastal, E., & Oliveira, M. (2011). Domain transform for edge-aware image and video processing. ACM TOG (SIGGRAPH), 30(4), 69:1–69:12. Gastal, E., & Oliveira, M. (2011). Domain transform for edge-aware image and video processing. ACM TOG (SIGGRAPH), 30(4), 69:1–69:12.
Zurück zum Zitat Gastal, E., & Oliveira, M. (2012). Adaptive manifolds for real-time high-dimensional filtering. ACM TOG (SIGGRAPH), 31(4), 33:1–33:13. Gastal, E., & Oliveira, M. (2012). Adaptive manifolds for real-time high-dimensional filtering. ACM TOG (SIGGRAPH), 31(4), 33:1–33:13.
Zurück zum Zitat Gilboa, G. (2014). A total variation spectral framework for scale and texture analysis. SIAM Journal of Imaging Sciences, 7(4), 1937–1961.MathSciNetCrossRefMATH Gilboa, G. (2014). A total variation spectral framework for scale and texture analysis. SIAM Journal of Imaging Sciences, 7(4), 1937–1961.MathSciNetCrossRefMATH
Zurück zum Zitat Gupta, S., Arbeláez, P. A., Girshick, R. B., & Malik, J. (2015). Indoor scene understanding with RGB-D images: Bottom-up segmentation, object detection and semantic segmentation. IJCV, 112(2), 133–149.MathSciNetCrossRef Gupta, S., Arbeláez, P. A., Girshick, R. B., & Malik, J. (2015). Indoor scene understanding with RGB-D images: Bottom-up segmentation, object detection and semantic segmentation. IJCV, 112(2), 133–149.MathSciNetCrossRef
Zurück zum Zitat He, K., Sun, J., & Tang, X. (2013). Guided image filtering. IEEE TPAMI, 35, 1397–1409.CrossRef He, K., Sun, J., & Tang, X. (2013). Guided image filtering. IEEE TPAMI, 35, 1397–1409.CrossRef
Zurück zum Zitat Karacan, L., Erdem, E., & Erdem, A. (2013). Structure-preserving image smoothing via region covariances. ACM TOG (SIGGRAPH Asia), 32(6), 176:1–176:11. Karacan, L., Erdem, E., & Erdem, A. (2013). Structure-preserving image smoothing via region covariances. ACM TOG (SIGGRAPH Asia), 32(6), 176:1–176:11.
Zurück zum Zitat Kivinen, J. J., Williams, C. K., & Heess, N. (2014). Visual boundary prediction: A deep neural prediction network and quality dissection. In AISTATS. Kivinen, J. J., Williams, C. K., & Heess, N. (2014). Visual boundary prediction: A deep neural prediction network and quality dissection. In AISTATS.
Zurück zum Zitat Kyprianidis, J. E., & Döllner, J. (2008). Image abstraction by structure adaptive filtering. In Proceedings of EG UK theory and practice of computer graphics, Manchester, United Kingdom, 2008 (pp. 51–58). Kyprianidis, J. E., & Döllner, J. (2008). Image abstraction by structure adaptive filtering. In Proceedings of EG UK theory and practice of computer graphics, Manchester, United Kingdom, 2008 (pp. 51–58).
Zurück zum Zitat Kyprianidis, J. E., & Kang, H. (2011). Image and video abstraction by coherence-enhancing filtering. Computer Graphics Forum, 30(2), 593–602.CrossRef Kyprianidis, J. E., & Kang, H. (2011). Image and video abstraction by coherence-enhancing filtering. Computer Graphics Forum, 30(2), 593–602.CrossRef
Zurück zum Zitat Levin, A., Lischinski, D., & Weiss, Y. (2006). A closed form solution to natural image matting. In CVPR. Levin, A., Lischinski, D., & Weiss, Y. (2006). A closed form solution to natural image matting. In CVPR.
Zurück zum Zitat Lim, J., Zitnick, C. L., & Dollár, P. (2013). Sketch tokens: A learned mid-level representation for contour and object detection. In CVPR. Lim, J., Zitnick, C. L., & Dollár, P. (2013). Sketch tokens: A learned mid-level representation for contour and object detection. In CVPR.
Zurück zum Zitat Lischinski, D., Farbman, Z., Uyttendaele, M., & Szeliski, R. (2006). Interactive local adjustment of tonal values. ACM TOG (SIGGRAPH), 25(3), 646–653.CrossRef Lischinski, D., Farbman, Z., Uyttendaele, M., & Szeliski, R. (2006). Interactive local adjustment of tonal values. ACM TOG (SIGGRAPH), 25(3), 646–653.CrossRef
Zurück zum Zitat Margolin, R., Zelnik-Manor, L., & Tal, A. (2014). How to evaluate foreground maps. In CVPR. Margolin, R., Zelnik-Manor, L., & Tal, A. (2014). How to evaluate foreground maps. In CVPR.
Zurück zum Zitat Meyer, Y. (2001). Oscillating Patterns in Image Processing and Nonlinear Evolution Equations: The Fifteenth Dean Jacqueline B. Lewis Memorial Lectures. Providence: American Mathematical Society.CrossRefMATH Meyer, Y. (2001). Oscillating Patterns in Image Processing and Nonlinear Evolution Equations: The Fifteenth Dean Jacqueline B. Lewis Memorial Lectures. Providence: American Mathematical Society.CrossRefMATH
Zurück zum Zitat Min, D., Choi, S., Lu, J., Ham, B., Sohn, K., & Do, M. N. (2014). Fast global image smoothing based on weighted least squares. IEEE TIP, 23(12), 5638–5653.MathSciNetMATH Min, D., Choi, S., Lu, J., Ham, B., Sohn, K., & Do, M. N. (2014). Fast global image smoothing based on weighted least squares. IEEE TIP, 23(12), 5638–5653.MathSciNetMATH
Zurück zum Zitat Paris, S., & Durand, F. (2009). A fast approximation of the bilateral filter using a signal processing approach. IJCV, 81, 24–52.CrossRef Paris, S., & Durand, F. (2009). A fast approximation of the bilateral filter using a signal processing approach. IJCV, 81, 24–52.CrossRef
Zurück zum Zitat Paris, S., Kornprobst, P., Tumblin, J., & Durand, F. (2009). Bilateral filtering: Theory and applications. Foundations and Trends in Computer Graphics and Vision, 4(1), 1–73.CrossRefMATH Paris, S., Kornprobst, P., Tumblin, J., & Durand, F. (2009). Bilateral filtering: Theory and applications. Foundations and Trends in Computer Graphics and Vision, 4(1), 1–73.CrossRefMATH
Zurück zum Zitat Parisand, S., Hasinoff, S. W., & Kautz, J. (2011). Local laplacian filters: Edge-aware image processing with a Laplacian pyramid. ACM TOG (SIGGRAPH), 30(4), 68:1–68:12. Parisand, S., Hasinoff, S. W., & Kautz, J. (2011). Local laplacian filters: Edge-aware image processing with a Laplacian pyramid. ACM TOG (SIGGRAPH), 30(4), 68:1–68:12.
Zurück zum Zitat Perazzi, F., Krahenbuhl, P., Pritch, Y., & Hornung, A. (2012). Saliency filters: Contrast based filtering for salient region detection. In CVPR (pp. 733–740). Perazzi, F., Krahenbuhl, P., Pritch, Y., & Hornung, A. (2012). Saliency filters: Contrast based filtering for salient region detection. In CVPR (pp. 733–740).
Zurück zum Zitat Perona, P., & Malik, J. (1990). Scale-space and edge detection using anisotropic diffusion. IEE TPAMI, 12, 629–639.CrossRef Perona, P., & Malik, J. (1990). Scale-space and edge detection using anisotropic diffusion. IEE TPAMI, 12, 629–639.CrossRef
Zurück zum Zitat Perreault, S., & Hbert, P. (2007). Median filtering in constant time. IEEE TIP, 16(9), 2389–2394.MathSciNet Perreault, S., & Hbert, P. (2007). Median filtering in constant time. IEEE TIP, 16(9), 2389–2394.MathSciNet
Zurück zum Zitat Petschnigg, G., Szeliski, R., Agrawala, M., Cohen, M., Hoppe, H., & Toyama, K. (2004). Digital photography with flash and no-flash image pairs. ACM TOG (SIGGRAPH), 23(3), 664–672.CrossRef Petschnigg, G., Szeliski, R., Agrawala, M., Cohen, M., Hoppe, H., & Toyama, K. (2004). Digital photography with flash and no-flash image pairs. ACM TOG (SIGGRAPH), 23(3), 664–672.CrossRef
Zurück zum Zitat Pham, T. Q., & van Vliet, L. J. (2005). Separable bilateral filtering for fast video preprocessing. In ICME. Pham, T. Q., & van Vliet, L. J. (2005). Separable bilateral filtering for fast video preprocessing. In ICME.
Zurück zum Zitat Porikli, F. (2008). Constant time o(1) bilateral filtering. In CVPR. Porikli, F. (2008). Constant time o(1) bilateral filtering. In CVPR.
Zurück zum Zitat Rhemann, C., Hosni, A., Bleyer, M., Rother, C., & Gelautz, M. (2011). Fast cost-volume filtering for visual correspondence and beyond. In CVPR. Rhemann, C., Hosni, A., Bleyer, M., Rother, C., & Gelautz, M. (2011). Fast cost-volume filtering for visual correspondence and beyond. In CVPR.
Zurück zum Zitat Ren, X., & Liefeng, B. (2012). Discriminatively trained sparse code gradients for contour detection. In NIPS. Ren, X., & Liefeng, B. (2012). Discriminatively trained sparse code gradients for contour detection. In NIPS.
Zurück zum Zitat Rudin, L. I., Osher, S., & Fatemi, E. (1992). Nonlinear total variation based noise removal algorithms. Physica D, 60(1–4), 259–268.MathSciNetCrossRefMATH Rudin, L. I., Osher, S., & Fatemi, E. (1992). Nonlinear total variation based noise removal algorithms. Physica D, 60(1–4), 259–268.MathSciNetCrossRefMATH
Zurück zum Zitat Shen, W., Wang, X., Wang, Y., Bai, X., & Zhang, Z. (2015). Deepcontour: A deep convolutional feature learned by positive-sharing loss for contour detection. In CVPR (pp. 3982–3991). Shen, W., Wang, X., Wang, Y., Bai, X., & Zhang, Z. (2015). Deepcontour: A deep convolutional feature learned by positive-sharing loss for contour detection. In CVPR (pp. 3982–3991).
Zurück zum Zitat Subr, K., Soler, C., & Durand, F. (2009). Edge-preserving multiscale image decomposition based on local extrema. ACM ToG (SIGGRAPH Asia), 28(5), 147. Subr, K., Soler, C., & Durand, F. (2009). Edge-preserving multiscale image decomposition based on local extrema. ACM ToG (SIGGRAPH Asia), 28(5), 147.
Zurück zum Zitat Tomasi, C., & Manduchi, R. (1998). Bilateral filtering for gray and color images. In ICCV (pp. 839–846). Tomasi, C., & Manduchi, R. (1998). Bilateral filtering for gray and color images. In ICCV (pp. 839–846).
Zurück zum Zitat Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004). Image quality assessment: From error visibility to structural similarity. IEEE TIP, 13(4), 600–612. Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004). Image quality assessment: From error visibility to structural similarity. IEEE TIP, 13(4), 600–612.
Zurück zum Zitat Weickert, J. (1999). Coherence-enhancing diffusion filtering. IJCV, 31(2–3), 111–127.CrossRef Weickert, J. (1999). Coherence-enhancing diffusion filtering. IJCV, 31(2–3), 111–127.CrossRef
Zurück zum Zitat Weiss, B. (2006). Fast median and bilateral filtering. ACM TOG (SIGGRAPH), 25(3), 519–526.CrossRef Weiss, B. (2006). Fast median and bilateral filtering. ACM TOG (SIGGRAPH), 25(3), 519–526.CrossRef
Zurück zum Zitat Xie, S., & Tu, Z. (2015). Holistically-nested edge detection. In Proceedings of IEEE international conference on computer vision. Xie, S., & Tu, Z. (2015). Holistically-nested edge detection. In Proceedings of IEEE international conference on computer vision.
Zurück zum Zitat Xu, K., Li, Y., Ju, T., Hu, S. M., & Liu, T. Q. (2009). Efficient affinity-based edit propagation using k-d tree. ACM ToG (SIGGRAPH Asia), 28(5), 118:1–118:6. Xu, K., Li, Y., Ju, T., Hu, S. M., & Liu, T. Q. (2009). Efficient affinity-based edit propagation using k-d tree. ACM ToG (SIGGRAPH Asia), 28(5), 118:1–118:6.
Zurück zum Zitat Xu, L., Lu, C., Xu, Y., & Jia, J. (2011). Image smoothing via l0 gradient minimization. ACM TOG (SIGGRAPH Asia), 36(6), 174. Xu, L., Lu, C., Xu, Y., & Jia, J. (2011). Image smoothing via l0 gradient minimization. ACM TOG (SIGGRAPH Asia), 36(6), 174.
Zurück zum Zitat Xu, L., Yan, Q., & Jia, J. (2013). A sparse control model for image and video editing. ACM TOG (SIGGRAPH Asia), 32(6), 197. Xu, L., Yan, Q., & Jia, J. (2013). A sparse control model for image and video editing. ACM TOG (SIGGRAPH Asia), 32(6), 197.
Zurück zum Zitat Xu, L., Yan, Q., Xia, Y., & Jia, J. (2012). Structure extraction from texture via relative total variation. ACM TOG (SIGGRAPH Asia), 31(6), 139. Xu, L., Yan, Q., Xia, Y., & Jia, J. (2012). Structure extraction from texture via relative total variation. ACM TOG (SIGGRAPH Asia), 31(6), 139.
Zurück zum Zitat Yan, Q., Xu, L., Shi, J., & Jia, J. (2013). Hierarchical saliency detection. In CVPR. Yan, Q., Xu, L., Shi, J., & Jia, J. (2013). Hierarchical saliency detection. In CVPR.
Zurück zum Zitat Yang, J., Price, B., Cohen, S., Lee, H., & Yang, M. H. (2016). Object contour detection with a fully convolutional encoder-decoder network. In CVPR. Yang, J., Price, B., Cohen, S., Lee, H., & Yang, M. H. (2016). Object contour detection with a fully convolutional encoder-decoder network. In CVPR.
Zurück zum Zitat Yang, Q. (2012). Recursive bilateral filtering. In ECCV (pp. 399–413). Yang, Q. (2012). Recursive bilateral filtering. In ECCV (pp. 399–413).
Zurück zum Zitat Yang, Q. (2016). Semantic filtering. In CVPR. Yang, Q. (2016). Semantic filtering. In CVPR.
Zurück zum Zitat Yang, Q., Ahuja, N., & Tan, K. (2015). Constant time median and bilateral filtering. IJCV, 112(3), 307–318.CrossRef Yang, Q., Ahuja, N., & Tan, K. (2015). Constant time median and bilateral filtering. IJCV, 112(3), 307–318.CrossRef
Zurück zum Zitat Yang, Q., Tan, K. H., & Ahuja, N. (2009). Real-time o(1) bilateral filtering. In CVPR (pp. 557–564). Yang, Q., Tan, K. H., & Ahuja, N. (2009). Real-time o(1) bilateral filtering. In CVPR (pp. 557–564).
Zurück zum Zitat Yang, Q., Wang, S., & Ahuja, N. (2010). Svm for edge-preserving filtering. In CVPR (pp. 1775–1782). Yang, Q., Wang, S., & Ahuja, N. (2010). Svm for edge-preserving filtering. In CVPR (pp. 1775–1782).
Zurück zum Zitat Yin, W., Goldfarb, D., & Osher, S. (2005). Image cartoon-texture decomposition and feature selection using the total variation regularized l1 functional. In VLSM (pp. 73–84). Yin, W., Goldfarb, D., & Osher, S. (2005). Image cartoon-texture decomposition and feature selection using the total variation regularized l1 functional. In VLSM (pp. 73–84).
Zurück zum Zitat Yoon, K. J., & Kweon, I. S. (2006). Adaptive support-weight approach for correspondence search. IEEE TPAMI, 28(4), 650–656.CrossRef Yoon, K. J., & Kweon, I. S. (2006). Adaptive support-weight approach for correspondence search. IEEE TPAMI, 28(4), 650–656.CrossRef
Zurück zum Zitat Zeune, L., van Dalum, G., Terstappen, L. W. M. M., van Gils, S. A., & Brune, C. (2016). Multiscale segmentation via Bregman distances and nonlinear spectral analysis. CoRR arXiv:1604.06665. Zeune, L., van Dalum, G., Terstappen, L. W. M. M., van Gils, S. A., & Brune, C. (2016). Multiscale segmentation via Bregman distances and nonlinear spectral analysis. CoRR arXiv:​1604.​06665.
Zurück zum Zitat Zhang, J., Sclaroff, S., Lin, Z., Shen, X., Price, B., & Mech, R. (2015). Minimum barrier salient object detection at 80 fps. In ICCV. Zhang, J., Sclaroff, S., Lin, Z., Shen, X., Price, B., & Mech, R. (2015). Minimum barrier salient object detection at 80 fps. In ICCV.
Zurück zum Zitat Zhang, Q., Shen, X., Xu, L., & Jia, J. (2014). Rolling guidance filter. In ECCV. Zhang, Q., Shen, X., Xu, L., & Jia, J. (2014). Rolling guidance filter. In ECCV.
Zurück zum Zitat Zheng, S., Tu, Z., & Yuille, A. (2007). Detecting object boundaries using low-,mid-, and high-level information. In CVPR. Zheng, S., Tu, Z., & Yuille, A. (2007). Detecting object boundaries using low-,mid-, and high-level information. In CVPR.
Zurück zum Zitat Ziou, D., & Tabbone, S. (1998). Edge detection techniques: An overview. IEEE TPAMI, 8, 537–559. Ziou, D., & Tabbone, S. (1998). Edge detection techniques: An overview. IEEE TPAMI, 8, 537–559.
Zurück zum Zitat Zitnick, C. L., & Dollár, P. (2014). Edge boxes: Locating object proposals from edges. In ECCV. Zitnick, C. L., & Dollár, P. (2014). Edge boxes: Locating object proposals from edges. In ECCV.
Zurück zum Zitat Zitnick, C. L., & Parikh, D. (2012). The role of image understanding in contour detection. In CVPR. Zitnick, C. L., & Parikh, D. (2012). The role of image understanding in contour detection. In CVPR.
Metadaten
Titel
Joint Contour Filtering
verfasst von
Xing Wei
Qingxiong Yang
Yihong Gong
Publikationsdatum
23.04.2018
Verlag
Springer US
Erschienen in
International Journal of Computer Vision / Ausgabe 11/2018
Print ISSN: 0920-5691
Elektronische ISSN: 1573-1405
DOI
https://doi.org/10.1007/s11263-018-1091-5

Weitere Artikel der Ausgabe 11/2018

International Journal of Computer Vision 11/2018 Zur Ausgabe