Abstract
For overcoming the shortcomings of total variation for image reconstruction, which easily smooth image texture, and produce lots of artificial edges, a non-smooth hybrid energy functional regularization model and iterative algorithm is proposed. Firstly, fitting term is described by L1 norm for blurred image by system and salt and pepper noise, regularization terms are described by fractional order bounded variation function semi-norm and L1 norm. Secondly, resorting to introduce auxiliary variables, the primal non-smooth energy functional regularization model without condition constraints is converted into energy functional regularization model with condition constraints, which is split into six easily computing sub-problems by the alternating direction method of multipliers (ADMM). Finally, alternating iterative six sub-problems, an improved image reconstruction algorithm is proposed. Numerical experiments show that the proposed model has advantages over several state-of-art approaches in terms of the reconstruction visual effect.
Highlights
In recent years, reconstruction blurred image by system and noise, the widespread acceptance is how to establish hybrid energy functional regularization model, which is composed of fitting term and regularization term [1]
For blurry image by salt and pepper noise, the image statistical distribution is described by L1 norm, the solution singularity property is described by bounded variation (BV) function [2]
The rest of this paper is organized as follows : In section 2, we review the tight frame theory and establish hybrid energy functional regularization model for reconstruction image blurred by system and salt and pepper noise
Summary
Reconstruction blurred image by system and noise, the widespread acceptance is how to establish hybrid energy functional regularization model, which is composed of fitting term and regularization term [1]. For reducing the stair effect of steady area of BV, reference [4] used the second BV for regularization term of image reconstruction model. The four order elliptic equation is obtained by energy functional regularization model of calculus of variation, which smears image edge. The rest of this paper is organized as follows : In section 2, we review the tight frame theory and establish hybrid energy functional regularization model for reconstruction image blurred by system and salt and pepper noise.
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