<title>New SNR estimate for the Wiener filter to image restoration</title>

Abstract

Image restoration is an estimation process that attempts to recover an ideal high quality image from a given degraded version. The Wiener filter method derived from the minimum mean square error criterion is widely used in image restoration to restore degraded images. In this method the constant (Gamma) , which is an a priori representation of the signal to noise ratio for the complete image plane, is unknown and its value is supplied by the user and adjusted by the trial and error approach. In this paper a new estimation process of (Gamma) is proposed. First of all, a second image is constructed from the given degraded image (referred to as the first image) using the Lagrange's interpolation technique. The Lagrange's interpolation technique used here is actually a modified version of the original approach. Secondly, an expression for (Gamma) [i, j], which is an a priori representation of the signal to noise ratio at pixel [i, j], is obtained using both the first and the second images and their auto correlations. However the Wiener filter only needs (Gamma) for the complete image plane. Therefore an arithmetic mean of a selected set of (Gamma) [i, j] values is calculated. This arithmetic mean is then used as (Gamma) in the Wiener filter to restore the first image.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.