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This study explores analytic rasterization of curves with polynomial filters for enhanced image sampling and pixel evaluation. The methodology involves filter integrals, piecewise boundaries, and scanline rasterization techniques. Researchers Josiah Manson and Scott Schaefer from Texas A&M University present a detailed derivation and implementation of this novel approach. The innovation offers constant color gradients and seamless image rendering.
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Analytic Rasterization of Curves with Polynomial Filters Josiah Manson and Scott Schaefer Texas A&M University
Motivation Constant colors Color gradients
Input Curve Boundary Piecewise Filter
Input [Duff, 1989] “Polygon scan conversion by exact convolution” [Manson and Schaefer, 2011] “Wavelet Rasterization” Curve Boundary Piecewise Filter
Image Sampling Image
Image Sampling Pixel positions
Image Sampling Evaluate at point
Image Sampling Center filter at point
Image Sampling Center filter at point
Image Sampling Center filter at point
Image Sampling Multiply
Image Sampling Integrate
Image Sampling Repeat for all pixels
Filter Integrals Zero C h a n g e s Zero Zero C h a n g e s Constant
ScanlineRasterization Changing
ScanlineRasterization Changing Constant