In many image resolution enhancement applications, the blurring process of the imaging system is unknown. This paper discusses the problem of single image blind resolution enhancement without estimating the point spread function (PSF). A regularization model is constructed for image enhancement based on the prior information of image error and image gray value, which does not need any prior information of PSF. Moreover, through the solution of Euler equations, and anisotropic nonlinear diffusion equation are obtained, which can avoid the high computational cost of regularization model. Furthermore, in order to get sub-pixel superresolved image, the regularization model for image enhancement is extended to the enlargement of image, which can enlarge and enhance image at the same time Last, to get clearer edges, a high frequency enhancement filter is used on the superresolved image Numerical results show that the new model can get much clearer super-resolution images than traditional methods, and the peak signal to noise ratios (PSNRs) are also higher than traditional methods.
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