Spline functions, because of their highly desirable interpolating and approximating characteristics, are used as a potential alternative to the conventional pulse approximation method in digital image processing. In space-invariant imaging systems, the object and point-spread function are represented by a class of spline functions called B-splines. Exploiting the convolutional property of B-splines, the deterministic part of the degraded image is another B-spline of higher degree. A minimum norm principle leading to pseudoinversion is used for the restoration of space-invariant degradations with underdetermined and overdetermined models. The singular-value-decomposition technique is used to determine the pseudoinverse.
© 1978 Optical Society of America
M. J. Peyrovian and A. A. Sawchuk, "Image restoration by spline functions," Appl. Opt. 17, 660-666 (1978)