Share Email Print
cover

Proceedings Paper

A new hyperspectral image compression paradigm based on fusion
Author(s): Raúl Guerra; José Melián; Sebastián López; Roberto Sarmiento
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The on-board compression of remote sensed hyperspectral images is an important task nowadays. One of the main difficulties is that the compression of these images must be performed in the satellite which carries the hyperspectral sensor. Hence, this process must be performed by space qualified hardware, having area, power and speed limitations. Moreover, it is important to achieve high compression ratios without compromising the quality of the decompress image. In this manuscript we proposed a new methodology for compressing hyperspectral images based on hyperspectral image fusion concepts. The proposed compression process has two independent steps. The first one is to spatially degrade the remote sensed hyperspectral image to obtain a low resolution hyperspectral image. The second step is to spectrally degrade the remote sensed hyperspectral image to obtain a high resolution multispectral image. These two degraded images are then send to the earth surface, where they must be fused using a fusion algorithm for hyperspectral and multispectral image, in order to recover the remote sensed hyperspectral image. The main advantage of the proposed methodology for compressing remote sensed hyperspectral images is that the compression process, which must be performed on-board, becomes very simple, being the fusion process used to reconstruct image the more complex one. An extra advantage is that the compression ratio can be fixed in advanced. Many simulations have been performed using different fusion algorithms and different methodologies for degrading the hyperspectral image. The results obtained in the simulations performed corroborate the benefits of the proposed methodology.

Paper Details

Date Published: 24 October 2016
PDF: 9 pages
Proc. SPIE 10007, High-Performance Computing in Geoscience and Remote Sensing VI, 100070F (24 October 2016); doi: 10.1117/12.2242891
Show Author Affiliations
Raúl Guerra, Institute of Applied Microelectronics (Spain)
José Melián, Institute of Applied Microelectronics (Spain)
Sebastián López, Institute of Applied Microelectronics (Spain)
Roberto Sarmiento, Institute of Applied Microelectronics (Spain)


Published in SPIE Proceedings Vol. 10007:
High-Performance Computing in Geoscience and Remote Sensing VI
Bormin Huang; Sebastián López; Zhensen Wu; Jose M. Nascimento; Jun Li; Valeriy V. Strotov, Editor(s)

© SPIE. Terms of Use
Back to Top