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16 December 1988 Image Restoration Via Iterative Improvement Of The Wiener Filter
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The Wiener filter has often been employed as a means for solving the signal/image restoration problem. Unfortunately, the information that is required as input for the realization of this filter is, in many practical situations, not available. In particular, when only one degraded, noisy observation of the signal is presented as data, the spectral density function for the signal to be recovered will generally not be known. A typical 'fix' to this dilemma has been to assume that the ratio of noise to signal spectral densities is constant with frequency. The value of this constant that makes the best reconstruction is then determined via trial-and-error by a human. In this paper we present an alternative to this over-simplified version of the Wiener filter (K-filter). Specifically, we demonstrate that an estimate of the signal spectral density can be made via an iterative procedure from the data. This results in reconstructions that are generally superior to any output that the simplified Wiener filter can provide. We show simulated results for the case of one-dimensional degradations of image data.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Charles V. Jakowatz Jr., Paul H. Eichel, and Dennis C. Ghiglia "Image Restoration Via Iterative Improvement Of The Wiener Filter", Proc. SPIE 0974, Applications of Digital Image Processing XI, (16 December 1988);


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