ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume II-3
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3, 41–48, 2014
https://doi.org/10.5194/isprsannals-II-3-41-2014
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3, 41–48, 2014
https://doi.org/10.5194/isprsannals-II-3-41-2014

  07 Aug 2014

07 Aug 2014

Fast global stereo matching via energy pyramid minimization

B. Conejo1,2, S. Leprince1, F. Ayoub1, and J. P. Avouac1 B. Conejo et al.
  • 1GPS Division, California Institute of Technology, Pasadena, CA, USA
  • 2Imagine Lab, Université Paris-Est, LIGM (UMR CNRS 8049), ENPC, 77455 Marne-la-Vallée, France

Keywords: Photogrammetry, Global, Matching, Multiresolution, Algorithms, Estimation, DEM/DTM

Abstract. We define a global matching framework based on energy pyramid, the Global Matching via Energy Pyramid (GM-EP) algorithm, which estimates the disparity map from a single stereo-pair by solving an energy minimization problem. We efficiently address this minimization by globally optimizing a coarse to fine sequence of sparse Conditional Random Fields (CRF) directly defined on the energy. This global discrete optimization approach guarantees that at each scale we obtain a near optimal solution, and we demonstrate its superiority over state of the art image pyramid approaches through application to real stereo-pairs. We conclude that multiscale approaches should be build on energy pyramids rather than on image pyramids.