Efficient High-Dimensional Filtering for Image and Video Processing

  • Eduardo S. L. Gastal UFRGS
  • Manuel M. Oliveira UFRGS

Resumo


High-dimensional filters are a fundamental building block for several applications, having recently received considerable attention from the research community. Unfortunately, naive implementations of such an important class of filters are too slow for many practical uses. This dissertation describes three novel approaches to efficiently perform high-dimensional filtering with linear cost in both the number of pixels and in the dimensionality of the space in which the filters operate. Our filters address the main limitations of previous techniques, in addition to providing the fastest performance (both on CPU and GPU) for a variety of real-world applications.

Referências

Adams, A., Baek, J., and Davis, M. A. (2010). Fast high-dimensional filtering using the permutohedral lattice. Computer Graphics Forum, 29(2):753–762.

Baek, J., Pajak, D., Kim, K., Pulli, K., and Levoy, M. (2013). Wysiwyg computational photography via viewfinder editing. ACM TOG, 32(6):198:1–198:10.

Barron, J. T., Adams, A., Shih, Y., and Hern´andez, C. (2015). Fast Bilateral-Space Stereo for Synthetic Defocus. In IEEE CVPR, pages 4466–4474.

Bauszat, P., Eisemann, M., and Magnor, M. (2011). Guided image filtering for interactive high-quality global illumination. Computer Graphics Forum, 30(4):1361–1368.

Bonneel, N., Sunkavalli, K., Paris, S., and Pfister, H. (2013). Example-based video color grading. ACM TOG, 32(4):39:1–39:12.

Buades, A., Coll, B., and Morel, J. (2005). A non-local algorithm for image denoising. In IEEE CVPR, volume 2, pages 60–65.

Fattal, R. (2009). Edge-avoiding wavelets and their applications. ACM TOG, 28(3):22.

Gastal, E. S. L. and Oliveira, M. M. (2011). Domain transform for edge-aware image and video processing. ACM TOG, 30(4):69:1–69:12. Proc. of SIGGRAPH 2011.

Gastal, E. S. L. and Oliveira, M. M. (2012). Adaptive manifolds for real-time highdimensional filtering. ACM TOG, 31(4):33:1–33:13. Proc. of SIGGRAPH 2012.

Gastal, E. S. L. and Oliveira, M. M. (2015). High-order recursive filtering of nonuniformly sampled signals for image and video processing. Computer Graphics Forum, 34(2):81–93. Proc. of Eurographics 2015.

Kopf, J., Cohen, M. F., Lischinski, D., and Uyttendaele, M. (2007). Joint bilateral upsampling. ACM TOG, 26:96:1–96:5.

Lang, M., Wang, O., Aydin, T., Smolic, A., and Gross, M. (2012). Practical temporal consistency for image-based graphics applications. ACM TOG, 31(4):34:1–34:8.

OpenCV (2016). Open Source Computer Vision library 3.0. http://opencv.org.

Smith, S. M. and Brady, J. M. (1997). SUSAN – a new approach to low level image processing. International Journal of Computer Vision, 23(1):45–78.

Winnemoller, H., Olsen, S. C., and Gooch, B. (2006). Real-time video abstraction. ACM TOG, 25(3):1226.

Yang, Q., Tan, K. H., and Ahuja, N. (2009). Real-time O(1) bilateral filtering. In CVPR, pages 557–564.
Publicado
04/07/2016
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GASTAL, Eduardo S. L.; OLIVEIRA, Manuel M.. Efficient High-Dimensional Filtering for Image and Video Processing. In: CONCURSO DE TESES E DISSERTAÇÕES (CTD), 29. , 2016, Porto Alegre. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2016 . p. 61-66. ISSN 2763-8820. DOI: https://doi.org/10.5753/ctd.2016.9140.