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Spatio-Temporal Image Processing: Theory and Scientific ApplicationsDecember 1993
Publisher:
  • Springer-Verlag
  • Berlin, Heidelberg
ISBN:978-0-387-57418-9
Published:01 December 1993
Pages:
208
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Abstract

No abstract available.

Cited By

  1. Wang C, Xu L and Liu L (2023). Structure–texture image decomposition via non-convex total generalized variation and convolutional sparse coding, The Visual Computer: International Journal of Computer Graphics, 39:3, (1121-1136), Online publication date: 1-Mar-2023.
  2. Zhou F, Chen Q, Liu B and Qiu G (2020). Structure and Texture-Aware Image Decomposition via Training a Neural Network, IEEE Transactions on Image Processing, 29, (3458-3473), Online publication date: 1-Jan-2020.
  3. Ding L, Huang H and Zang Y (2017). Image Quality Assessment Using Directional Anisotropy Structure Measurement, IEEE Transactions on Image Processing, 26:4, (1799-1809), Online publication date: 1-Apr-2017.
  4. Márquez-Valle P, Gil D and Hernàndez-Sabaté A Error analysis for lucas-kanade based schemes Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part I, (184-191)
  5. Yu Y, Mann G and Gosine R (2010). An object-based visual attention model for robotic applications, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 40:5, (1398-1412), Online publication date: 1-Oct-2010.
  6. Heindlmaier M, Yu L and Diepold K The impact of nonlinear filtering and confidence information on optical flow estimation in a Lucas & Kanade framework Proceedings of the 16th IEEE international conference on Image processing, (1573-1576)
  7. Ren W, Singh S, Singh M and Zhu Y (2009). State-of-the-art on spatio-temporal information-based video retrieval, Pattern Recognition, 42:2, (267-282), Online publication date: 1-Feb-2009.
  8. Preusser T, Scharr H, Krajsek K and Kirby R (2008). Building Blocks for Computer Vision with Stochastic Partial Differential Equations, International Journal of Computer Vision, 80:3, (375-405), Online publication date: 1-Dec-2008.
  9. Olsen O and Nielsen M (2006). The Generic Structure of the Optic Flow Field, Journal of Mathematical Imaging and Vision, 24:1, (37-53), Online publication date: 1-Jan-2006.
  10. Scharr H Diffusion-Like reconstruction schemes from linear data models Proceedings of the 28th conference on Pattern Recognition, (51-60)
  11. Arseneau S and Cooperstock J An improved representation of junctions through asymmetric tensor diffusion Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I, (363-372)
  12. ACM
    Agrawal A, Raskar R, Nayar S and Li Y Removing photography artifacts using gradient projection and flash-exposure sampling ACM SIGGRAPH 2005 Papers, (828-835)
  13. Gil D, Hernandez A, Carol A, Rodriguez O and Radeva P A deterministic-statistic adventitia detection in IVUS images Proceedings of the Third international conference on Functional Imaging and Modeling of the Heart, (65-74)
  14. ACM
    Agrawal A, Raskar R, Nayar S and Li Y (2005). Removing photography artifacts using gradient projection and flash-exposure sampling, ACM Transactions on Graphics, 24:3, (828-835), Online publication date: 1-Jul-2005.
  15. Scharr H Towards a multi-camera generalization of brightness constancy Proceedings of the 1st international conference on Complex motion, (78-90)
  16. Scharr H Optimal filters for extended optical flow Proceedings of the 1st international conference on Complex motion, (14-29)
  17. Jähne B Complex motion in environmental physics and live sciences Proceedings of the 1st international conference on Complex motion, (91-103)
  18. Ngo C, Pong T and Zhang H (2019). Motion-Based Video Representation for Scene Change Detection, International Journal of Computer Vision, 50:2, (127-142), Online publication date: 1-Nov-2002.
  19. Yu W, Sommer G, Beauchemin S and Daniilidis K (2002). Oriented Structure of the Occlusion Distortion, IEEE Transactions on Pattern Analysis and Machine Intelligence, 24:9, (1286-1290), Online publication date: 1-Sep-2002.
  20. López A, Lumbreras F, Serrat J and Villanueva J (1999). Evaluation of Methods for Ridge and Valley Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, 21:4, (327-335), Online publication date: 1-Apr-1999.
  21. Bab-Hadiashar A and Suter D (2019). Robust Optic Flow Computation, International Journal of Computer Vision, 29:1, (59-77), Online publication date: 1-Aug-1998.
Contributors
  • Heidelberg University
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