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Morphological operations on color images

Morphological image processing has been widely used to process binary and grayscale images, with morphological techniques being applied to noise reduction, image enhancement, and feature detection. Relying on an ordering of the data, morphology modifies the geometrical aspects of an image: object contours in binary images and object surfaces in grayscale images. Extending morphological operators to color image processing has been problematic because it is not easy to define geometry of a vector-valued function and ordering of vectors is not straightforward. We propose a new set of color morphological operators based on a combination of reduced ordering and conditional ordering of the underlying data.