Image Pyramids Pre-filter images to collect information at different scalesPre-filter images to collect information at different scales More efficient.

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Presentation transcript:

Image Pyramids Pre-filter images to collect information at different scalesPre-filter images to collect information at different scales More efficient computation, allows larger motionsMore efficient computation, allows larger motions

Image Pyramids Szeliski

Pyramid Creation “Gaussian” Pyramid“Gaussian” Pyramid “Laplacian” Pyramid“Laplacian” Pyramid – Created from Gaussian pyramid by subtraction L i = G i – expand(G i+1 ) Szeliski

Octaves in the Spatial Domain Bandpass Images Lowpass Images Szeliski

Blending Blend over too small a region: seamsBlend over too small a region: seams Blend over too large a region: ghostingBlend over too large a region: ghosting

Multiresolution Blending Different blending regions for different levels in a pyramid [Burt & Adelson]Different blending regions for different levels in a pyramid [Burt & Adelson] – Blend low frequencies over large regions (minimize seams due to brightness variations) – Blend high frequencies over small regions (minimize ghosting)

Pyramid Blending Szeliski

Minimum-Cost Cuts Instead of blending high frequencies along a straight line, blend along line of minimum differences in image intensitiesInstead of blending high frequencies along a straight line, blend along line of minimum differences in image intensities

Minimum-Cost Cuts Moving object, simple blending  blur [Davis 98]

Minimum-Cost Cuts Minimum-cost cut  no blur [Davis 98]

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