Intrinsic Images by Entropy Minimization

By Graham David Finlayson, Mark Samuel Drew, Cheng Lu. European Conference on Computer Vision, 2004

332 citations recorded by the source corpus.

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Removing photography artifacts using gradient projection and flash-exposure sampling (2005, methodology): “We use the observation that the orientation of image gradients remains stable under variable illumination if the gradients are due to local changes in reflectance and geometric shape and not due to local changes in illumination [Lichtenauer et al. 2004; Finlayson et al. 2004].”
On the removal of shadows from images (2006, methodology): “Logcolour ratios then live on a plane in 3-space orthogonal to u = (1,1,1)T and form lines exactly as in Fig. 1a [ 35 ].”
Road Detection Based on Illuminant Invariance (2011, methodology): “Moreover, the results provided by (green) our method and (blue) the entropy-based method [18] are also shown. instance, Fig.”
Intrinsic Decompositions for Image Editing (2017, unknown): “This is often implemented by clustering lines of log-RGB pixel values, similar to the color lines model [OW04] (though not performed in the log-domain), or via entropy minimization [FDL04].”
Entropy Minimization for Shadow Removal (2009, background): “8 (see Finlayson et al. 2004): ρ · u = 0.”