2005, 1(2):144-147.
Abstract:
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.
Supported by the National Natural Science Foundation of China (No. 60272013) and National Excellent Doctoral Dissertation
Fund of China (No. 200140)