TITLE:
An Improved EZW Hyperspectral Image Compression
AUTHORS:
Kai-Jen Cheng, Jeffrey C. Dill
KEYWORDS:
Wavelet Transform; Karhunen-Loève Transform; Transform-based Image Compression; AVIRIS Hyperspectral Image; Embedded Zerotree Wavelet
JOURNAL NAME:
Journal of Computer and Communications,
Vol.2 No.2,
January
10,
2014
ABSTRACT:
The paper describes an efficient lossy and
lossless three dimensional (3D) image compression of hyperspectral images. The
method adopts the 3D spatial-spectral hybrid transform and the proposed
transform-based coder. The hybrid transforms are that Karhunen-Loève Transform (KLT) which decorrelates spectral data of a hyperspectral
image, and the integer Discrete Wavelet Transform (DWT) which is applied to the
spatial data and produces decorrelated wavelet coefficients. Our simpler
transform-based coder is inspired by Shapiro’s EZW algorithm, but encodes
residual values and only implements dominant pass incorporating six symbols.
The proposed method will be examined on AVIRIS images and evaluated using compression ratio for both lossless and lossy compression,
and signal to noise ratio (SNR) for lossy compression. Experimental results
show that the proposed image compression not only is more efficient but also
has better compression ratio.