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Image super-resolution is a process to enhance image resolution. It is widely used in medical imaging, satellite imaging, target recognition, etc. In this paper, we conduct continuous modeling and assume that the unknown image intensity function is d efined on a continuous domain and belongs to a space with a redundant basis. We propose a new iterative model for single image super-resolution based on an observation: an image is consisted of smooth components and non-smooth components, and we use two classes of approximated Heaviside functions (AHFs) to represent them respectively. Due to sparsity of the non-smooth components, a $L_{1}$ model is employed. In addition, we apply the proposed iterative model to image patches to reduce computation and storage. Comparisons with some existing competitive methods show the effectiveness of the proposed method.
We investigate the fluctuation effect of the di-fermion field in the crossover from Bardeen-Cooper-Schrieffer (BCS) pairing to a Bose-Einstein condensate (BEC) in a relativistic superfluid. We work within the boson-fermion model obeying a global U(1) symmetry. To go beyond the mean field approximation we use Cornwall-Jackiw-Tomboulis (CJT) formalism to include higher order contributions. The quantum fluctuations of the pairing condensate is provided by bosons in non-zero modes, whose interaction with fermions gives the two-particle-irreducible (2PI) effective potential. It changes the crossover property in the BEC regime. With the fluctuations the superfluid phase transition becomes the first order in grand canonical ensemble. We calculate the condensate, the critical temperature $T_{c}$ and particle abundances as functions of crossover parameter the boson mass.
We propose a general derivation of differential cross section in quark-quark scatterings at fixed impact parameters. The derivation is well defined and free of ambiguity in the conventional one. The approach can be applied to a variety of partonic an d hadronic scatterings in low or high energy particle collisions.
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