Morphological gradient operators for colour images

A new morphological gradient operator for colour images is introduced that can be viewed as a direct extension of the well known morphological gradient. In this approach, each pixel is considered as multivariate data and its output is the maximum distance between any two points within a structuring element, determined by a norm. In contrast with other nonlinear schemes, this approach reduces to the morphological gradient for single channel images. It is also computationally efficient and responds well to step edges. To overcome, any sensitivity to noise a robust colour morphological gradient operator is proposed that rejects outlying vector pairs before determining the maximum distance. Results show the effectiveness of the techniques.