Edge-based color constancy makes use of image derivatives
to estimate the illuminant. However, different edge
types exist in real-world images such as shadow, geometry,
material and highlight edges. These different edge types
may have a distinctive inf luence on the performance of the
illuminant estimation.
Therefore, in this paper, an extensive analysis is provided
of different edge types on the performance of edge-based
color constancy methods. First, an edge-based taxonomy is
presented classifying edge types based on their ref lectance
properties (e.g. material, shadow-geometry and highlights).
Then, a performance evaluation of edge-based color constancy
is provided using these different edge types. From
this performance evaluation, it is derived that certain edge
types are more valuable than material edges for the estimation
of the illuminant. To this end, the weighted Grey-Edge
algorithm is proposed in which certain valuable edge types
are more emphasized for the ...