Illumination Correction for Stitching Images
Sascha Klement, Fabian Timm, and Erhardt Barth
Here, we provide additional material concerning our submission
"Illumination Correction for Stitching Images" for the ICPR 2010. The
following table shows input images with different textures under varying
lighting conditions and the results after illumination correction with
the the three studied boundary conditions.
Remarks:
 All input images were captured using a Baumer TXG14c camera (1392 x 1040 pixels)
 We
focused on the reduction of boundary artifacts when removing
illumination inhomogeneities, not on a perfect stitching of the
corrected images. So for tiling, the images were simply placed in a
3by3 matrix without any further processing. Thus, repetitive patterns
are obvious even with polynomial regression, but they are not caused by
illumination inhomogeneities.
 With the replicate boundary
condition dark areas at the image transitions are clearly visible.
Linear extrapolation reduces these boundary artifact significantly.
Polynomial LeastSquares Regression gives no further visible
improvements but is mathematically the more stable method.
 To get the fullresolution image, click on an image.
Input Image

Corrected and
Tiled Image (Replicate Boundary)

Corrected and
Tiled Image (Linear Extrapolation)

Corrected and Tiled Image (Polynomial LeastSquares Regression)

















