Local image restoration by a least-squares method

Restoration of individual image points by the method of least squares is investigated. We show that restorations computed point by point appear the same as global restorations produced by Fourier techniques. Moreover, parameters that are related to noise, point-spread functions, or object texture can be varied easily from pixel to pixel, allowing a flexibility that is achieved only with computational difficulty in global restoration techniques. To restore individual pixels, only a few points in their neighborhood, need to be considered, and the matrices that must be inverted are small enough for practical computation. The sizes of these matrices can be reduced especially if the blurring point-spread function has symmetries.