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computed. These DFT values are interpreted as samples of the FT of g x; y on a regular polar lattice, as shown in Figure 18.5 [Dudgeon]. These samples are interpolated to yield estimates on a rectangular lattice. Finally, the 2-D inverse DFT is computed to obtain g m; n . Usually, the size of the inverse DFT is chosen as two to three times that of each dimension of g m; n . Appropriate windowing as discussed in Section 14.2 before the inverse DFT allows the minimization of the effects of Fourier domain truncation. The simplest approach to interpolation is zeroth order or linear interpolation. Each desired rectangular sample point fx ; fy is surrounded by four polar samples. In zeroth order interpolation, the rectangular sample is assigned the value of the nearest polar sample. In linear interpolation, a weighted average of the four nearest polar samples is used. The weighting can be taken inversely proportional to the Euclidian distance between the points. A simple method is to use bilinear interpolation in terms of the polar coordinates: let f ; y be the coordinates of the point at which the interpolated sample is desired; let fi ; yj , i; j 1; 2 denote the coordinates of the four nearest polar samples. Then, the bilinear interpolation can be written as G f ; y winforms upc-a reader Packages matching Tags:"UPC-A" - NuGet Gallery
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