Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Since digital images are usually sparse in the wavelet frame domain, some nonconvex minimization models based on wavelet frame have been proposed and sparse approximations have been widely used in image restoration in recent years. Among them, the proximal alternating iterative hard thresholding method is proposed in this paper to solve the nonconvex model based on wavelet frame. Through combining the proposed algorithm with the iterative hard thresholding algorithm which is ll studied in compressed sensing theory, this paper proves that the complexity of the proposed method is            O   (  1  /    k    )        . On the other hand, a more general nonconvex–nonsmooth model is adopted and the pseudo proximal alternating linearized minimization method is developed to solve the above problem. With the Kurdyka–Łojasiewicz (KL) property, it is proved that the sequence generated by the proposed algorithm converges to some critical points of the corresponding model. Finally, the proposed method is applied to restore the blurred noisy gray images. As the numerical results reveal, the performance of the proposed method is comparable or better than some ll-known convex image restoration methods.
['Fan Yang', 'Yi Shen', 'Zhi Song Liu']
I am writing a research paper on a idea The proximal alternating iterative hard thresholding method for l 0 minimization, with complexity.
[{"from": "human", "value": "I am writing a research paper on a idea The proximal alternating iterative hard thresholding method for l 0 minimization, with complexity."}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Since digital images are usually sparse in the wavelet frame domain, some nonconvex minimization models based on wavelet frame have been proposed and sparse approximations have been widely used in image restoration in recent years. Among them, the proximal alternating iterative hard thresholding method is proposed in this paper to solve the nonconvex model based on wavelet frame. Through combining the proposed algorithm with the iterative hard thresholding algorithm which is ll studied in compressed sensing theory, this paper proves that the complexity of the proposed method is            O   (  1  /    k    )        . On the other hand, a more general nonconvex\u2013nonsmooth model is adopted and the pseudo proximal alternating linearized minimization method is developed to solve the above problem. With the Kurdyka\u2013\u0141ojasiewicz (KL) property, it is proved that the sequence generated by the proposed algorithm converges to some critical points of the corresponding model. Finally, the proposed method is applied to restore the blurred noisy gray images. As the numerical results reveal, the performance of the proposed method is comparable or better than some ll-known convex image restoration methods."}]