Least-squares image resizing using finite differences
Journal
IEEE Transactions on Image Processing
Journal Volume
10
Journal Issue
9
Date Issued
2001-09-01
Author(s)
Abstract
We present an optimal spline-based algorithm for the enlargement or reduction of digital images with arbitrary (noninteger) scaling factors. This projection-based approach can be realized thanks to a new finite difference method that allows the computation of inner products with analysis functions that are B-splines of any degree n. A noteworthy property of the algorithm is that the computational complexity per pixel does not depend on the scaling factor a. For a given choice of basis functions, the results of our method are consistently better than those of the standard interpolation procedure; the present scheme achieves a reduction of artifacts such as aliasing and blocking and a significant improvement of the signal-to-noise ratio. The method can be generalized to include other classes of piecewise polynomial functions, expressed as linear combinations of B-splines and their derivatives.
Subjects
Affine transform | Boundary conditions | Finite difference | Interpolation | Least-squares | Oblique projection | Scale spline
Type
journal article