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Seamless Image Stitching in the Gradient Domain. Levin, Zomet, Peleg and Weiss ECCV 2004. Image Stitching. Capturing different portions of the same scene with an overlap region viewed in both images Keep mosaic as similar as possible to original both geometrically and photometrically
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Seamless Image Stitching in the Gradient Domain Levin, Zomet, Peleg and Weiss ECCV 2004
Image Stitching • Capturing different portions of the same scene with an overlap region viewed in both images • Keep mosaic as similar as possible to original both geometrically and photometrically • The seam between the images should be invisible
Image Stitching Overlap Regions
Previous Approaches • Optimal Seam • Search for a curve in the overlap region on which the differences between the images is minimal • Poorly handles global intensity differences
Previous Approaches • Feathering • Smooth the transition by weighting alpha mask as a function of the distance from the seam • Poorly handles misalignments
Previous Approaches • Pyramid Blending • Combine different frequency bands with different alpha masks • Poorly handles misalignments
Common Problems Global Intensity Difference Horizontal Misalignment Vertical Misalignment
New Approach : GIST Goal: Minimize the dissimilarity between the derivatives of the images Gradient-domain Image STitching (GIST) Take two aligned input images, overlap them, minimize the distance between their derivatives.
GIST I1 I2
GIST • Initialize the solution image I • Iterate until convergence • For all x,y in the image, update I(x,y) to be:
GIST Advantages • Invariant to the mean intensity of the image • Less sensitive to smooth global differences • Penalizes inconsistent derivatives • Where I1 and I2 have low gradients, penalizes for high gradients in mosaic.
Results Optimal Seam Feathering Pyramid Blending Optimal seam on gradients Feathering on gradients Pyramid blending on gradients Poisson GIST1
Results Optimal Seam Feathering Pyramid Blending Optimal seam on gradients Feathering on gradients Pyramid blending on gradients Poisson GIST1
Plan • Take pictures ( 1 day ) • Implement ( 2 weeks ) • Optimal Cut • Feathering • Pyramid Blending • Implement ( 1 week ) • GIST • Compare ( 1 week ) • Applications ( 1 week )
Efros, A., Freeman, W.: Image quilting for texture synthesis and transfer. Proceedings of SIGGRAPH 2001 (2001) 341–346 • Adelson, E.H., Anderson, C.H., Bergen, J.R., Burt, P.J., M., O.J.: Pyramid method in image processing. RCA Engineer 29(6) (1984) 33–41 • Uyttendaele, M., Eden, A., Szeliski, R.: Eliminating ghosting and exposure artifacts in image mosaics. In: CVPR. (2001) II:509–516