Anisotropic nonlinear diffusion approach to image sharpening

In many image resolution enhancement applications, the blurring process of the imaging system is unknown. In this paper we discuss the problem of image sharpening without estimating the point spread function (PSF). A regularization model is constructed based on the prior information of image error and image gray value, which does not need any prior of PSF. The regularization model is translated to an anisotropic nonlinear diffusion equation by solving its Euler equation, which can avoid the high computational cost of regularization model. Furthermore, to get clearer edges, a high frequency enhancement filter is used on the image superresolved by nonlinear diffusion equation. Numerical results show that the new model can get much clearer superresolution images than traditional methods, and the peak signal to noise ratios (PSNRs) are also higher than traditional methods.