21 June 2015 Stereo matching based on census transformation of image gradients
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Although multiple-view matching provides certain significant advantages regarding accuracy, occlusion handling and radiometric fidelity, stereo-matching remains indispensable for a variety of applications; these involve cases when image acquisition requires fixed geometry and limited number of images or speed. Such instances include robotics, autonomous navigation, reconstruction from a limited number of aerial/satellite images, industrial inspection and augmented reality through smart-phones. As a consequence, stereo-matching is a continuously evolving research field with growing variety of applicable scenarios. In this work a novel multi-purpose cost for stereo-matching is proposed, based on census transformation on image gradients and evaluated within a local matching scheme. It is demonstrated that when the census transformation is applied on gradients the invariance of the cost function to changes in illumination (non-linear) is significantly strengthened. The calculated cost values are aggregated through adaptive support regions, based both on cross-skeletons and basic rectangular windows. The matching algorithm is tuned for the parameters in each case. The described matching cost has been evaluated on the Middlebury stereo-vision 2006 datasets, which include changes in illumination and exposure. The tests verify that the census transformation on image gradients indeed results in a more robust cost function, regardless of aggregation strategy.
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C. Stentoumis, C. Stentoumis, L. Grammatikopoulos, L. Grammatikopoulos, I. Kalisperakis, I. Kalisperakis, G. Karras, G. Karras, E. Petsa, E. Petsa, } "Stereo matching based on census transformation of image gradients", Proc. SPIE 9528, Videometrics, Range Imaging, and Applications XIII, 95280Q (21 June 2015); doi: 10.1117/12.2184763; https://doi.org/10.1117/12.2184763

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