%0 Journal Article
	%A Lewis E. Hibell and  Honghai Liu and  David J. Brown
	%D 2007
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 12, 2007
	%T Enhancing Multi-Frame Images Using Self-Delaying Dynamic Networks
	%U https://publications.waset.org/pdf/4055
	%V 12
	%X This paper presents the use of a newly created network
structure known as a Self-Delaying Dynamic Network (SDN) to
create a high resolution image from a set of time stepped input
frames. These SDNs are non-recurrent temporal neural networks
which can process time sampled data. SDNs can store input data
for a lifecycle and feature dynamic logic based connections between
layers. Several low resolution images and one high resolution image
of a scene were presented to the SDN during training by a Genetic
Algorithm. The SDN was trained to process the input frames in order
to recreate the high resolution image. The trained SDN was then used
to enhance a number of unseen noisy image sets. The quality of high
resolution images produced by the SDN is compared to that of high
resolution images generated using Bi-Cubic interpolation. The SDN
produced images are superior in several ways to the images produced
using Bi-Cubic interpolation.
	%P 4026 - 4031