Image coarsening by using space-filling curve for decomposition-based image enhancement

We propose a novel space-filling curve based image coarsening method, which automatically extracts a base-layer from an input image while still preserving its structural context, meaningful details, et cetera. In the proposed method, specifically, a one-dimensional edge-preserving smoothing filter, which is called a vector ε-filter, is applied to an input image along a space-filling curve. In this regard, the space-filling curve is constructed by using a minimum spanning tree which extracts the structural context of the input image. This novel image coarsening approach is completely different from all conventional approaches employing any kind of two-dimensional filter window. Furthermore, this coarsening method can effectively produce an aggregation of texture details as well as enhance sharp edges, while preserving structural contexts such as thin lines and sharp corners. The main benefit of the coarsened image by the proposed method is its suitability for extracting fine features of an input image for decomposition-based image enhancement. In this paper, the structural-context-preserving image coarsening capability of the proposed method is verified by some results from experiments and examples. Then we show our new method’s characteristics in practical application to decomposition-based image enhancement by using some other examples.