Improved fixed point method for image restoration

We analyze the fixed point method with Tikhonov regularization under the periodic boundary conditions, and propose a changable regularization parameter method. Firstly, we choose a bigger one to restrain the noise in the reconstructed image, and get a convergent result to modify the initial gradient. Secondly, we choose a smaller one to increase the details in the image. Experimental results show that compared with other popular algorithms which solve the L₁ norm regularization function and Total Variation(TV) regularization function, the improved fixed point method performs favorably in solving the problem of the motion degradation and Gaussian degradation.