Generalized proximal conjugate gradient method for image deblurring

It is very difficult to restore natural geometry of the actual image from degraded observation. In this paper, to deal with approximation error and the turbulence casued by proximal splitting scheme, a generalized proximal conjugate gradient framework is proposed. To trade off approximate accuracy and computational complexity, an approximate solution is presented, which characterized by maintaining the sparse pattern of second-derivate information and considered a correcting stage with conjugate gradient. Some theoretical properties of the proposed method are discussed and presented. The numerical experiments of the proposed algorithm, in compassion to the favorable state-of-the-art methods, demonstrate the advantages of the proposed method and its great potential.

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