Fast image interpolation using Circular Harmonic Functions

In this paper we introduce a novel edge directed image interpolation algorithm so as to obtain an high-resolution image, given a low-resolution image. The interpolation is based on the local image directionality features estimated on the low-resolution image. The in depth analysis of the local edge features is accomplished at a low computational cost by filtering the low-resolution image by means of the first order filter belonging to the class of the Circular Harmonic Functions (CHF). The interpolation algorithm shows low computational complexity. Numerical results show that the CHF-driven interpolation outperforms state of the art estimators from both a subjective and objective point of view, in several simulation conditions.

[1]  Giovanni Jacovitti,et al.  Multiresolution circular harmonic decomposition , 2000, IEEE Trans. Signal Process..

[2]  Alessandro Neri,et al.  Blind image deconvolution using Bussgang techniques: Applications to deblurring and texture synthesis , 2007 .

[3]  Patrizio Campisi,et al.  Multichannel blind image deconvolution using the Bussgang algorithm: spatial and multiresolution approaches , 2003, IEEE Trans. Image Process..

[4]  M. Unser,et al.  Interpolation revisited [medical images application] , 2000, IEEE Transactions on Medical Imaging.

[5]  Alessandro Neri.  Optimal detection and estimation of straight patterns , 1996, IEEE Trans. Image Process..

[6]  Alessandro Neri,et al.  Multiscale image features analysis with circular harmonic wavelets , 1995, Optics + Photonics.

[7]  J. Besag.  Spatial Interaction and the Statistical Analysis of Lattice Systems , 1974 .

[8]  Stéphane Mallat,et al.  Wavelets for a vision , 1996, Proc. IEEE.

[9]  Truong Q. Nguyen,et al.  Markov Random Field Model-Based Edge-Directed Image Interpolation , 2007, IEEE Transactions on Image Processing.

[10]  J. Besag,et al.  Bayesian image restoration, with two applications in spatial statistics , 1991 .

[11]  Ron Kimmel,et al.  Demosaicing: Image Reconstruction from Color CCD Samples , 1998, ECCV.

[12]  Jing Li,et al.  Restoration and reconstruction from overlapping images for multi-image fusion , 2001, IEEE Trans. Geosci. Remote. Sens..

[13]  Thomas Martin Deserno,et al.  Survey: interpolation methods in medical image processing , 1999, IEEE Transactions on Medical Imaging.

[14]  Yücel Altunbasak,et al.  Super-resolution reconstruction of hyperspectral images , 2005 .

[15]  M. Unser,et al.  Interpolation Revisited , 2000, IEEE Trans. Medical Imaging.

[16]  Patrizio Campisi,et al.  Blind Image Deblurring Driven by Nonlinear Processing in the Edge Domain , 2004, EURASIP J. Adv. Signal Process..