A multiplicative iterative algorithm for box-constrained penalized likelihood image restoration
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Description
• Image restoration is a computationally intensive problem as a large number of pixel values have to be determined. • Since the pixel values of digital images can attain only a finite number of values. • In this paper, develop a new box-constrained multiplicative iterative (BCMI) algorithm for box-constrained image restoration. • The BCMI algorithm just requires pixel wise updates in each iteration, and there is no need to invert any matrices. • Then give the convergence proof of this algorithm and apply it to total variation image restoration problems, where the observed blurry images contain Poisson, Gaussian, or salt-and-pepper noises.
Tags: 2012, Image processing, Matlab