1 research outputs found
Visual Data Deblocking using Structural Layer Priors
The blocking artifact frequently appears in compressed real-world images or
video sequences, especially coded at low bit rates, which is visually annoying
and likely hurts the performance of many computer vision algorithms. A
compressed frame can be viewed as the superimposition of an intrinsic layer and
an artifact one. Recovering the two layers from such frames seems to be a
severely ill-posed problem since the number of unknowns to recover is twice as
many as the given measurements. In this paper, we propose a simple and robust
method to separate these two layers, which exploits structural layer priors
including the gradient sparsity of the intrinsic layer, and the independence of
the gradient fields of the two layers. A novel Augmented Lagrangian Multiplier
based algorithm is designed to efficiently and effectively solve the recovery
problem. Extensive experimental results demonstrate the superior performance of
our method over the state of the arts, in terms of visual quality and
simplicity