The invention discloses a
pigment separation method of centralized image channel difference based on
optical density space, which comprises the following steps of acquiring an RGB
color skin image under polarized light and extracting
skin color; dividing the image into a plurality of sub-image blocks and discarding the sub-image blocks containing non-
skin pixels; obtaining the pure color density of each sub-image block; obtaining a matrix optimum
solid color concentration matrix; calculating the concentrations of
melanin and
hemoglobin in the image, and introducing the gray distribution and color distribution of the
pigment concentration. According to the present invention, a
light source interference term in a conventional
pigment separation model is eliminated without principal componentanalysis, and a simple and efficient constraint condition for judging the rationality of the pure color concentration matrix is designed, thereby avoiding, in the existing pigment
separation algorithm, the inaccuracy and robustness of the pigment concentration extraction result due to the interference of
light source intensity and the
data loss in the
principal component analysis process, as wellas the low efficiency of the
algorithm due to the complexity of the determination process of the pure color concentration matrix.