A fast algorithm for binary image restoration

In this paper, we consider the problem to recover a binary digital image u ∈ R^m×n when the observed image g is corrupted with noise such as Gaussian or salt and pepper. By explicitly using the a priori knowledge for binary image, we propose a novel minimization model. Based on this new model, we present a novel fast iterative projection algorithm for binary image restoration. The main computation at each iteration is one fast Fourier transform (FFT) and one inverse fast Fourier transform (IFFT). Experimental results show that the proposed method is feasible and effective for binary image restoration. All of the results can be obtained within one second.