A Weighted Jacobi iteration based algebraic technique is proposed for smoothing discrete data, e.g., signal, image or video on grids with arbitrary topology. Energy of the discrete data is defined in $H^1$-space and a requirement for discrete scale-space theory is proposed based on the non-increase of energetic norm of the data. A shape-preserving smoothing method is also derived using a combination of Jacobi smoothers. Scale-selective smoothing of the data is achieved by eigenanalysis of the stiffness matrix. Experimental results are shown for isotropic image data.
By: Sugata Ghosal
Published in: International Conference on Pattern Recognition (ICIP 2000), Barcelona, Spain, September 2000., unknown in 2000
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