Abstract

In this paper we describe a digital method for restoring linearly degraded images in the presence of noise. The restoration procedure is an iterative regularized pseudoinverse (RPI) algorithm that is based on the principle of least squares. This method acquires the advantage of tolerance to noise by incorporating additional constraints of non-negativity of the object and adaptive regularization. We also use a median filter in the proposed algorithm to suppress spiky noise. We present some results of computer simulations that include both space-invariant and space-variant degradations. The effectiveness of the iterative RPI method is demonstrated through computer simulations.

© 1984 Optical Society of America

Restoration of band-limited images by an iterative regularized pseudoinverse method

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