Abstract
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.
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Gibson, S., Harvey, R., Finlayson, G. (2003). Convex Colour Sieves. In: Griffin, L.D., Lillholm, M. (eds) Scale Space Methods in Computer Vision. Scale-Space 2003. Lecture Notes in Computer Science, vol 2695. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44935-3_38
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DOI: https://doi.org/10.1007/3-540-44935-3_38
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