期刊名称：International Journal of Computer Science & Information Technology (IJCSIT)
印刷版ISSN：0975-4660
电子版ISSN：0975-3826
出版年度：2011
卷号：3
期号：1
语种：English
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Due to the factors like processing power limitation
s and channel capabilities images are often down
sampled and transmitted at low bit rates resulting
in a low resolution compressed image. High resoluti
on
images can be reconstructed from several blurred, n
oisy and down sampled low resolution images using
a computational process know as super resolution re
construction. Super-resolution is the process of
combining multiple aliased low-quality images to pr
oduce a high resolution, high-quality image. The
problem of recovering a high resolution image progr
essively from a sequence of low resolution
compressed images is considered. In this paper we p
ropose a novel DCT based progressive image display
algorithm by stressing on the encoding and decoding
process. At the encoder we consider a set of low
resolution images which are corrupted by additive w
hite Gaussian noise and motion blur. The low
resolution images are compressed using 8 by 8 block
s DCT and noise is filtered using our proposed nove
l
zonal filter. Multiframe fusion is performed in ord
er to obtain a single noise free image. At the deco
der
the image is reconstructed progressively by transmi
tting the coarser image first followed by the detai
l
image. And finally a super resolution image is reco
nstructed by applying our proposed novel adaptive
interpolation technique. We have performed both obj
ective and subjective analysis of the reconstructed
image, and the resultant image has better super res
olution factor, and a higher ISNR and PSNR. A
comparative study done with Iterative Back Projecti
on (IBP) and Projection on to Convex Sets
(POCS),Papoulis Grechberg, FFT based Super resolut
ion Reconstruction shows that our method has out
performed the previous contributions.
关键词：Adaptive Interpolation; DCT; Multiframe Fusion; Pro
gressive Image Transmission; Super Resolution;
Zonal Filter.
