Super-resolution of grey-level images by inverse diffusion processes

Algorithms for resolution enhancement are needed in various applications of image processing and communication such as compression, and HDTV, in which the enhancement of low resolution images acquired by CCD-based electronic cameras is required. We develop a geometric algorithm, based on diffusion processes, which are used both for smoothing of the enlarged image, when 'time' is flowing forward, and for enhancement. The latter is accomplished by allowing the 'time' to flow backwards, i.e. by 'solving' an inverse diffusion problem which is ill posed. In order to stabilize the flow as well as to enhance important features (e.g. edges) on the expense of less important image domains, we use modified and regularized Beltrami type diffusion equation.