Скачать или смотреть VMVW02 | Prof. Raymond Chan | A Nuclear-norm Model for Multi-Frame Super-resolution Reconstruction

VMVW02 | Prof. Raymond Chan | A Nuclear-norm Model for Multi-Frame Super-resolution Reconstruction

Speaker: Professor Raymond Chan (Chinese University of Hong Kong)
Date: 3rd Nov 2017 - 11:10 to 12:00
Venue: INI Seminar Room 1
Title: A Nuclear-norm Model for Multi-Frame Super-resolution Reconstruction
Event: (VMVW02) Generative models, parameter learning and sparsity
Abstract: In this talk, we give a new variational approach to obtain super-resolution
images from multiple low-resolution image frames extracted from video clips.
First the displacement between the low-resolution frames and the reference
frame are computed by an optical flow algorithm. The displacement matrix
is then decomposed into product of two matrices corresponding to the integer and fractional
displacement matrices respectively. The integer displacement matrices give rise to a non-convex
low-rank prior which is then convexified to give the nuclear-norm regularization
term. By adding a standard 2-norm data fidelity term to it, we obtain our proposed
nuclear-norm model. Alternating direction method of multipliers can then be used
to solve the model. Comparison of our method with other models on synthetic
and real video clips shows that our resulting images are more accurate
with less artifacts. It also provides much finer and discernable details.

Joint work with Rui Zhao. Research supported by HKRGC.

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