A biologically inspired algorithm for the recovery of shading and reflectance images.
We present an algorithm for separating the shading and reflectance images of photographed natural scenes. The algorithm exploits the constraint that in natural scenes chromatic and luminance variations that are co-aligned mainly arise from changes in surface reflectance, whereas near-pure luminance variations mainly arise from shading and shadows. The novel aspect of the algorithm is the initial separation of the image into luminance and chromatic image planes that correspond to the luminance, red-green, and blue-yellow channels of the primate visual system. The red-green and blue-yellow image planes are analysed to provide a map of the changes in surface reflectance, which is then used to separate the reflectance from shading changes in both the luminance and chromatic image planes. The final reflectance image is obtained by reconstructing the chromatic and luminance-reflectance-change maps, while the shading image is obtained by subtracting the reconstructed luminance-reflectance image from the original luminance image. A number of image examples are included to illustrate the successes and limitations of the algorithm.
Olmos
Andriana
A
McGill Vision Research, Department of Ophthalmology, McGill University, Montreal, Quebec H3A 1A1, Canada. adriana.olmos@mcgill.ca
Kingdom
Frederick A A
FA
D000465:Algorithms; D000818:Animals; D003118:Color Perception; D015350:Contrast Sensitivity; D003867:Depth Perception; D008027:Light; D008433:Mathematics; D010364:Pattern Recognition, Visual; D010775:Photic Stimulation / Q000379:methods; D011323:Primates / Q000502:physiology*; D014796:Visual Perception