TITLE:
New Results in Perceptually Lossless Compression of Hyperspectral Images
AUTHORS:
Chiman Kwan, Jude Larkin
KEYWORDS:
Hyperspectral Images (HSI), Compression, Perceptually Lossless, Principal Component Analysis (PCA), Human Visual System (HVS), PSNR, SSIM, JPEG-2000, X264, X265, Daala
JOURNAL NAME:
Journal of Signal and Information Processing,
Vol.10 No.3,
August
26,
2019
ABSTRACT:
Hyperspectral images (HSI) have hundreds of bands, which impose heavy
burden on data storage and transmission bandwidth. Quite a few compression
techniques have been explored for HSI in the past decades. One high performing
technique is the combination of principal component analysis (PCA)
and JPEG-2000 (J2K). However, since there are several new compression codecs
developed after J2K in the past 15 years, it is worthwhile to revisit this research
area and investigate if there are better techniques for HSI compression.
In this paper, we present some new results in HSI compression. We aim at
perceptually lossless compression of HSI. Perceptually lossless means that the
decompressed HSI data cube has a performance metric near 40 dBs in terms of
peak-signal-to-noise ratio (PSNR) or human visual system (HVS) based metrics.
The key idea is to compare several combinations of PCA and video/
image codecs. Three representative HSI data cubes were used in our studies.
Four video/image codecs, including J2K, X264, X265, and Daala, have
been investigated and four performance metrics were used in our comparative
studies. Moreover, some alternative techniques such as video, split band, and
PCA only approaches were also compared. It was observed that the combination
of PCA and X264 yielded the best performance in terms of compression
performance and computational complexity. In some cases, the PCA + X264
combination achieved more than 3 dBs than the PCA + J2K combination.