WANG Xuanze, PAN Han, JING Zhongliang. Imagesuper-resolution via hybrid regularization methods[J]. 2018, 50(10): 66-71.
DOI:
WANG Xuanze, PAN Han, JING Zhongliang. Imagesuper-resolution via hybrid regularization methods[J]. 2018, 50(10): 66-71.DOI: 10.11918/j.issn.0367-6234.201708047.
Imagesuper-resolution via hybrid regularization methods
Transform-invariant group-sparse regularization with directional total variation is an efficient method to solve the super-resolution problem in the regions with highly structured straight edges which is deformed from the real urban scenes and space scenes. Total variation
however
probably leads to staircase artifacts
which may affect the result of super-resolution to large extent. In this paper
we present a new method by mixing different regularizers
especially by combining wavelet analysis with the Transform invariant directional total variation objective function. This allows us to simultaneously recover textures and local geometry structures
particularly highly structured straight edges. To solve this hybrid regularization problem with different norms
we used the idea of templates for first-order conic solvers
and derived the solution of the whole object function that we proposed. Experiments on same real image collections show that our method is more effective than prior works.