Colour morphological sieves for scale-space image processing

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Convex Colour Sieves

Sieves and their variants are established processors for simplifying greyscale images. Because combined outputs of these filters satisfy the scale-space causality property they are often referred to as scale-space filters although they have quite different characteristics compared to systems based around diffusion. In this paper we implement several possible extensions of sieves for colour images which include: applying the processor on separate channels; and enforcing an ordering on the colour vectors. We show that a new definition, based on convex hulls in colour space, can lead to an effective algorithm. As with the greyscale method, the colour sieve produces a tree-based representation of image that form the first step to a meaningful hierarchical decomposition