The paper discusses the restoration method for motion-blurred images. The large errors observed in inverse filter or Wiener filter restorations of images are mainly due to the fact that a truncated region of image data is available for processing. Wiener filter is less sensitive to noise than inverse filter for the restorations of motionblurred images. However

there is a large error component

called the edge error

that arises due to the fact that real images seldom have the periodicity assumed by discrete Fourier transform operation. Optimal windows for image restoration are designed on the basis of mathematical expressions for the restoration errors. With these optimal windows

near-perfect restorations can be obtained except the narrow L-shape border at the right and bottom edges of the image

which we have to sacrifice for reduction of restoration errors over the rest of the image. The images that vary gradually in intensity near their borders have the best results

as demonstrated in actual restorations of test images. The paper also proves that we can only directly setup two dimensional point spread function

instead of first restoring in x direction and then in y direction. A procedure for estimating point spread functions of real-world motion-blurred images is provided in this paper.