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An improved Newton projection method for nonnegative deblurring of Poisson-corrupted images with Tikhonov regularization. (English) Zbl 1241.65059
Summary: A quasi-Newton projection method for image deblurring is presented. The image restoration problem is mathematically formulated as a nonnegatively constrained minimization problem where the objective function is the sum of the Kullback-Leibler divergence, used to express fidelity to the data in the presence of Poisson noise, and of a Tikhonov regularization term. The Hessian of the objective function is approximated so that the Newton system can be efficiently solved by using Fast Fourier Transforms. The numerical results show the potential of the proposed method both in terms of relative error reduction and computational efficiency.
MSC:
65K05Mathematical programming (numerical methods)
90C30Nonlinear programming
90C53Methods of quasi-Newton type
94A08Image processing (compression, reconstruction, etc.)
Software:
KELLEY
References:
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