TY  - JOUR
T1  - Lossy Compression of Hyperspectral Images Using Real-Time Technique
AU - Hasan, Haitham S. AU - Alsharqi, Mais A. 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 13
SP  - 4430
EP  - 4434
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.4430.4434
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.4430.4434
KW  - Fractal encoding
KW  -prediction
KW  -lossy compression
KW  -hyper-spectral image
KW  -exploit
KW  -technique
AB  - Several proposed methods related to Hyper-Spectral (HS) image compression have been published
in the recent years. These methods have often effective compression accuracy but they are time-consuming.
This study introduces the development of a real-time practical scheme for use in lossy HS image compression.
This scheme includes two parts; hardware using the Field Programmable Gate Array (FPGA) system and
software utilizing the band prediction and fractal encoding techniques. The software technique starts by
partitioning the HS image into a number of Groups of Bands (GoBs). Then, the first band in each GoB is utilized
by the intra-band prediction to exploit the spatial correlation. And the other bands in each GoB are employed
by the inter-band fractal coding technique as well as a limited search algorithm to make a complete benefit from
the local matching between any two neighboring bands. This technique shows that the reconstructed image
has a better improvement in the classification accuracy than the primary uncompressed image but still
time-consuming. So, to overcome this problem, the technique is implemented by using the FPGA. This hardware
technique is extremely suitable for real-time purposes.
ER  -