New SNR estimate for the Wiener filter to image restoration

Shan Suthaharan

doi:10.1117/12.171072

23 March 1994 New SNR estimate for the Wiener filter to image restoration

Shan Suthaharan

Proceedings Volume 2182, Image and Video Processing II; (1994) https://doi.org/10.1117/12.171072
Event: IS&T/SPIE 1994 International Symposium on Electronic Imaging: Science and Technology, 1994, San Jose, CA, United States

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.

Citation Download Citation

Shan Suthaharan "New SNR estimate for the Wiener filter to image restoration", Proc. SPIE 2182, Image and Video Processing II, (23 March 1994); https://doi.org/10.1117/12.171072

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KEYWORDS

Image restoration

Filtering (signal processing)

Image processing

Signal to noise ratio

Digital image processing

Image filtering

Point spread functions

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