Title :
Deblurring the discrete Gaussian blur
Author :
Mair, B.A. ; Wilson, David C. ; Réti, Zoltán
Author_Institution :
Dept. of Math., Florida Univ., Gainesville, FL, USA
Abstract :
In 1995 Z. Reti presented a method for deblurring images blurred by the discrete Gaussian. The method is based on theorems borrowed from analytic number theory developed by Gauss, G. Jacobi (1829), and Ramanujan. One advantage of this method over similar ones developed for the continuous domain is that it provides exact formulas for the deblurring convolution. In addition, while deblurring the Gaussian in the continuous domain is an ill-posed inverse problem, deblurring the discrete Gaussian model results in a mathematically well-posed problem. The formulas presented here provide error bounds which relate the quality of the reconstructed image to that of the blurred image. This deblurring method is conveniently expressed in terms of multiplication by Toeplitz matrices whose diagonal entries decrease exponentially, thus rendering the method suitable for numerical approximations. Condition numbers are provided for various choices of σ
Keywords :
Gaussian distribution; Toeplitz matrices; error analysis; focusing; image processing; image reconstruction; image sequences; inverse problems; number theory; transforms; G. Jacobi; Ramanujan; analytic number theory theorems; condition numbers; continuous domain; deblurring convolution; diagonal entries; discrete Gaussian blur; error bounds; exact formulas; ill-posed inverse problem; image deblurring method; mathematically well-posed problem; numerical approximations; reconstructed image quality; Convolution; Error analysis; Fourier transforms; Frequency; Gaussian processes; Image reconstruction; Jacobian matrices; Mathematical model; Mathematics; Rendering (computer graphics);
Conference_Titel :
Mathematical Methods in Biomedical Image Analysis, 1996., Proceedings of the Workshop on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-8186-7368-0
DOI :
10.1109/MMBIA.1996.534079