Low Complexity DCT-based DSC approach forHyperspectral Image Compression with Arithmetic Code
This paper proposes low complexity codec for lossy compression
on a sample hyperspectral image. These images have two kinds
of redundancies: 1) spatial; and 2) spectral. A discrete cosine
transform (DCT)- based Distributed Source Coding(DSC)
paradigm with Arithmetic code for low complexity is introduced.
Here, Set-partitioning based approach is applied to reorganize
DCT coefficients into wavelet like tree structure as Setpartitioning
works on wavelet transform, and extract the sign,
refinement, and significance bitplanes. The extracted refinement
bits are Arithmetic encoded, then by applying low density parity
check based (LDPC-based) Slepian-Wolf coder is implement to
our DSC strategy. Experimental results for SAMSON
(Spectroscopic Aerial Mapping System with Onboard
Navigation) data show that proposed scheme achieve peak signal
to noise ratio and compression to a very good extent for water
cube compared to building, land or forest cube.
Keywords: Image compression; hyperspectral image; distributed source coding (DSC); discrete cosine transform (DCT); Arithmetic code; low complexity.
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ABOUT THE AUTHORS
Meena Babu Vallakati
She received her bachelor’s degree in electronics and telecommunication engineering from North Maharashtra University, Maharashtra, India, in May 2008. From 2008 to 2011, she was with Rizvi College of engineering as Lecturer. She is currently pursuing master’s degree in electronics and telecommunication from Mumbai University and currently working at VIVA institute of Technology, Mumbai, India. Her area of interest is in the field of image compression.
R. R. Sedamkar
He received his bachelor’s degree in computer science engineering in 1991, masters degree in Computer science engineering in 1997 and the Ph.D. degree in 2010. He is currently Dean-Academics, Professor and Head of Computer Department at Thakur college of engineering and technology, Mumbai. His area of interests is Networking and Image compression.
Meena Babu Vallakati
She received her bachelor’s degree in electronics and telecommunication engineering from North Maharashtra University, Maharashtra, India, in May 2008. From 2008 to 2011, she was with Rizvi College of engineering as Lecturer. She is currently pursuing master’s degree in electronics and telecommunication from Mumbai University and currently working at VIVA institute of Technology, Mumbai, India. Her area of interest is in the field of image compression.
R. R. Sedamkar
He received his bachelor’s degree in computer science engineering in 1991, masters degree in Computer science engineering in 1997 and the Ph.D. degree in 2010. He is currently Dean-Academics, Professor and Head of Computer Department at Thakur college of engineering and technology, Mumbai. His area of interests is Networking and Image compression.
