In this paper we propose a blind deconvolusion method to enhance the resolution of images obtained by near-field microwave nondestructive techniques using an open ended rectangular waveguide probe. In fact, we model such imags to be the result of a convolution of the real input images with a point spread function (PSF). This PSF depends mainly on the dimensions of the waveguide, the operating frequency, the nature of the object under test and standoff distance between the waveguide and the object. Unfortunately, it is very difficult to model this PSF from the physical data. For this reason, we consider the problem as a blind deconvolution. The proposed method is based on regularization, and the solution is obtained iteratively, by successive estimation of the input and the PSF. The algorithm is initialized with a PSF obtained from a very simplified physical model. The performance of the proposed method is evaluated on some real data. Several examples of real image enhancement will be presented.
[1]
Reza Zoughi,et al.
Preliminary Study of the Influences of Effective Dielectric Constant and Nonuniform Probe Aperture Field Distribution on near Field Microwave Images
,
1997
.
[2]
Reginald L. Lagendijk,et al.
Identification and restoration of noisy blurred images using the expectation-maximization algorithm
,
1990,
IEEE Trans. Acoust. Speech Signal Process..
[3]
Bobby R. Hunt,et al.
Bayesian Methods in Nonlinear Digital Image Restoration
,
1977,
IEEE Transactions on Computers.
[4]
Richard M. Leahy,et al.
An optimal technique for constraint-based image restoration and reconstruction
,
1986,
IEEE Trans. Acoust. Speech Signal Process..