V.P. Potapov, S.E. Popov High-performance bands interleave conversion algorithm of EO-1 Hyperion data sensor
V.P. Potapov, S.E. Popov High-performance bands interleave conversion algorithm of EO-1 Hyperion data sensor


This paper presents high-performance algorithms for radiometric calibration procedures and bands interleave conversion. The article discusses a number of activities aimed at optimizing the algorithms preand post-processing of multi- and hyperspectral images. Proposed algorithm providing the ability to run them on multiprocessor platforms in multi-threaded mode, and ensure effective implementation on low I/O systems. Proposed the implementation of proportional reading image data in memory, followed by the placement of the values of radiance in the target buffer arrays in a few streams, calculated by the number of spectral bands or the number of lines of the image. The paper describes an ENVI extension, implementing the algorithms developed, technology-based GUI-WIDGETS integration with Java SwingX packages. To interact with the Java-classes that implement the logic of the presented algorithm, used Java-Bridge IDL technology.


Bands interleave conversion, multi-threading, java, IDL-Bridge

PP. 76-83.


1. Adler-Golden S.M., Perkins T., Matthew M.W., Berk A., Bernstein L.S., et al. Speed and accuracy improvements in FLAASH atmospheric correction of hyperspectral imagery// SPIE Optical Engineering. 2012. Vol. 51(11). P. 111707(1-10).
2. BIL, BIP, and BSQ raster files. [Elektronnyy resurs] // ESRI. ArcGIS 9.2 Desktop Help. URL:,_BIP,_and_BSQ_raster_files (data obrashcheniya 22.07.2014).
3. EarthExplorer [Elektronnyy resurs] // USGS. URL: (data obrashcheniya 22.07.2014).
4. Fast Line-of-sight Atmospheric Analysis of Hypercubes (FLAASH) [Elektronnyy resurs] // Exelis ENVI. URL: (data obrashcheniya 24.07.2014).
5. Hyperion level 1gst (L1GST) product output files data format control book. Earth Observing-1 (EO-1). Version 1.0. Department of the Interior U.S. Geological Survey. 2006. 24 P.
6. Perkins T., Adler-Golden S.M., Cappelaere P., Mandl D. High-speed Atmospheric Correction for Spectral Image Processing // SPIE Proceeding: Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII. 2012. Vol. 8390. P. 245-252
7. Qu Z., Goetz A. F. H., Kindel B. High-accuracy atmospheric correction for hyperspectral data (HATCH) model // Geoscience and Remote Sensing. 2003. Vol. 41(6). P. 1223 - 1231.
8. San B. T., Suzen M. L. Evaluation of different atmospheric correction algorithms for EO-1 Hyperion imagery // International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science. Tokyo. 2010. Vol. 38(8), P. 392-397.
9. The IDL Thread Pool [Elektronnyy resurs] // Exelis ENVI. URL: The__Thread_Pool.html (data obrashcheniya 29.09.2014)
10. Thompson B.J., Rahman Z., Park S.K. Multiscale retinex for improved performance in multispectral image classification // SPIE Proceedings: Visual Information Processing IX. 2000. Vol. 4041. P. 34-44.

2020 / 02
2020 / 01
2019 / 04
2019 / 03

© ФИЦ ИУ РАН 2008-2018. Создание сайта "РосИнтернет технологии".