A traditional solution of area-based stereo uses some kind of windowed pixel intensity correlation. This approach suffers from discretization artifacts which corrupt the correlation value. We introduce a new correlation statistic, which is completely invariant to image sampling, moreover it naturally provides a position of the correlation maximum between pixels. Hereby we can obtain sub-pixel disparity directly from sampling invariant and highly discriminable measurements without any postprocessing of the discrete disparity map. The key idea behind is to represent the image point neighbourhood in a different way, as a response to a bank of Gabor filters. The images are convolved with the filter bank and the complex correlation statistic (CCS) is evaluated from the responses without iterations. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Čech, J., & Šára, R. (2005). Complex correlation statistic for dense stereoscopic matching. In Lecture Notes in Computer Science (Vol. 3540, pp. 598–608). Springer Verlag. https://doi.org/10.1007/11499145_61
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