Non-blind Image Restoration Based on Convolutional Neural Network

Blind image restoration processors based on convolutional neural network (CNN) are intensively researched because of their high performance. However, they are too sensitive to the perturbation of the degradation model. They easily fail to restore the image whose degradation model is slightly different from the trained degradation model. In this paper, we propose a non-blind CNN-based image restoration processor, aiming to be robust against a perturbation of the degradation model compared to the blind restoration processor. Experimental comparisons demonstrate that the proposed non-blind CNN-based image restoration processor can robustly restore images compared to existing blind CNN-based image restoration processors.Comment: Accepted by IEEE 7th Global Conference on Consumer Electronics, 201

Jet-cloud interations and the brightening of the narrow line region in Seyfert galaxies

We study the kinematical and brightness evolution of emission line clouds in the narrow line region (NLR) of Seyfert galaxies during the passage of a jet. We derive a critical density above which a cloud remains radiative after compression by the jet cocoon. The critical density depends mainly on the cocoon pressure. Super-critical clouds increase in emission line brightness, while sub-critical clouds generally are highly overheated reducing their luminosity below that of the inter-cloud medium. Due to the pressure stratification in the bow-shock of the jet, a cylindrical structure of nested shells develops around the jet. The most compact and brightest compressed clouds surround the cloud-free channel of the radio jet. To support our analytical model we present a numerical simulation of a supersonic jet propagating into a clumpy NLR. The position-velocity diagram of the simulated H_alpha emission shows total line widths of the order of 500 km/s with large-scale variations in the radial velocities of the clouds due to the stratified pressure in the bow-shock region of the jet. Most of the luminosity is concentrated in a few dense clouds surrounding the jet. These morphological and kinematic signatures are all found in the well observed NLR of NGC1068 and other Seyfert galaxies.Comment: 11 pages, 3 figures, accepted for publication in The Astrophysical Journal Letter