A Class of Variational Model for Inverse Problem in Image Zooming
一类针对图像放大中反问题的变分模

To a mass of computation iteration of Chambolle model in solving the inverse problem of image zooming, a class of new model that is based on Besov space is put forward. The new model translates the variational problem that is solved into a sequence based wavelet field through the equivalence between Besov semi-norm and the norm of wavelet coefficients. And the process of minimization shows that the optimization solutions of the sequence can be represented as the orthogonal projection onto wavelet field. Finally, not only the zoomed images have sharper and smooth edges, but also the details of images are kept, resulting in the naturalness. In addition, the effect of denoising is very satisfactory.