Digital Image Processing
An address generator of a pseudo-Hilbert scan in a rectangle region
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Edge-preserving decompositions for multi-scale tone and detail manipulation
ACM SIGGRAPH 2008 papers
Edge-avoiding wavelets and their applications
ACM SIGGRAPH 2009 papers
Edge-preserving multiscale image decomposition based on local extrema
ACM SIGGRAPH Asia 2009 papers
Smoothed local histogram filters
ACM SIGGRAPH 2010 papers
Domain transform for edge-aware image and video processing
ACM SIGGRAPH 2011 papers
A new algorithm for N-dimensional Hilbert scanning
IEEE Transactions on Image Processing
Artistic Edge and Corner Enhancing Smoothing
IEEE Transactions on Image Processing
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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 @e-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.