NEURAL SMOOTHERS FOR NOISED DYNAMIC IMAGE SEQUENCES
Rastislav Lukáč - Csaba Stupák - Stanislav Marchevský
This paper is focused to exploit neural networks as smoothers
for noised dynamic image sequences. For the learning capability
and noise suppression property, the neural networks are very
popular and widely used in smoothing applications. In addition,
thanks to the development of VLSI technology, the implementation
of neural networks is simple. In this paper, three approaches of
networking are presented. Thus, the neural network as the
temporal, spatial and spatiotemporal filter is proposed. The
well-known and very popular backpropagation algorithm is used.
The performance of neural smoothers for dynamic image sequence
is evaluated through objective criteria and compared with
traditional temporal, spatial and spatiotemporal medians.
Keywords: neural networks, image processing, backpropagation, smoother, median