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R. Szeliski, "Fast Surface Interpolation Using Hierarchical Basis Functions," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, no. 6, pp. 513528, June, 1990.  
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@article{ 10.1109/34.56188, author = {R. Szeliski}, title = {Fast Surface Interpolation Using Hierarchical Basis Functions}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {12}, number = {6}, issn = {01628828}, year = {1990}, pages = {513528}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.56188}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  Fast Surface Interpolation Using Hierarchical Basis Functions IS  6 SN  01628828 SP513 EP528 EPD  513528 A1  R. Szeliski, PY  1990 KW  conjugate gradient; picture processing; surface interpolation; hierarchical basis functions; multigrid relaxation; convergence; smoothing levels; convergence of numerical methods; interpolation; picture processing; relaxation theory VL  12 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
An alternative to multigrid relaxation that is much easier to implement and more generally applicable is presented. Conjugate gradient descent is used in conjunction with a hierarchical (multiresolution) set of basis functions. The resultant algorithm uses a pyramid to smooth the residual vector before the direction is computed. Simulation results showing the speed of convergence and its dependence on the choice of interpolator, the number of smoothing levels, and other factors are presented. The relationship of this approach to other multiresolution relaxation and representation schemes is also discussed.
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