Spline-based Image Interpolators and Decimators: Design and Efficient Implementation
نویسندگان
چکیده
This tutorial paper addresses the problem of high-quality resizing that is arbitrary-scale conversion of images cast as projection of the underlying function on spline-like spaces. Such spaces are determined by the corresponding bases, which fully determine the quality of scale conversion. In our setting, the spacegenerating functions are chosen from the class of piecewise (spline-based) basis functions of minimal support constructed as combinations of uniform B-splines of different degrees. The benefit of such functions is that they allow for various effective optimization strategies and are also very efficient in practical implementation. Specifically, we present a minimax optimization technique for designing effective reconstruction functions specified in Fourier domain and demonstrate its performance by comparing with other designs in terms of error kernel behavior and by interpolation experiments with real images. We present also two efficient schemes for interpolation and decimation respectively based on the designed reconstruction kernels and comment on practical implementation issues.
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