Haitham S.  Hasan, Mais A.  Alsharqi, 
    Lossy Compression of Hyperspectral Images Using Real-Time Technique,
    Journal of Engineering and Applied Sciences,
    Volume 14,Issue 13,
    2019,
    Pages 4430-4434,
    ISSN 1816-949x,
    jeasci.2019.4430.4434,
    (https://makhillpublications.co/view-article.php?doi=jeasci.2019.4430.4434)
    Abstract: 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.
    Keywords: Fractal encoding;prediction;lossy compression;hyper-spectral image;exploit;technique