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Hyperspectral Image Compression

Recent Paper

Aaron B. Kiely and Matthew A. Klimesh, "Exploiting Calibration-Induced Artifacts in Lossless Compression of Hyperspectral Imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 47, no. 8, pp. 2672–2678, Aug. 2009. [PDF]

Abstract – Algorithms for compression of hyperspectral data are commonly evaluated on a readily available collection of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) images. These images are the end product of processing raw data from the instrument, and their sample value distributions contain artificial regularities that are introduced by the conversion of raw data values to radiance units. It is shown that some of the best reported lossless compression results for these images are achieved by algorithms that significantly exploit these artifacts. This fact has not been widely reported and may not be widely recognized. Compression performance comparisons involving such algorithms and these standard AVIRIS images can be misleading if they are extrapolated to images that lack such artifacts, such as unprocessed hyperspectral images. In fact, two of these algorithms are shown to achieve rather unremarkable compression performance on a set of more recent AVIRIS images that do not contain appreciable calibration-induced artifacts. This newer set of AVIRIS images, which contains both calibrated and raw images, is made available for compression experiments. To underscore the potential impact of exploiting calibration-induced artifacts in the standard AVIRIS datasets, a compression algorithm is presented that achieves noticeably smaller compressed sizes for these datasets than is reported for any other algorithm.

AVIRIS Hyperspectral Images

The most widely used images for benchmarking hyperspectral image compression algorithms are the standard 1997 AVIRIS calibrated radiance images.

Calibrated and uncalibrated AVIRIS images have been provided to the Consultative Committee for Space Data Systems (CCSDS) Multispectral and Hyperspectral Data Compression (MHDC) working group for compression testing and evaluation. This newer AVIRIS data, summarized in the table below, consists of five calibrated and corresponding 16-bit raw images acquired over Yellowstone, WY in 2006, as well as two additional 12-bit uncalibrated images. Each image is a 512-line scene containing 224 spectral bands. False-color previews of these images can be seen here.

Site Scene Numbers Flight Year Samples/Line Bit Depth Data Type
Yellowstone, WY 0, 3, 10, 11, 18 f060925t01p00r12 2006 680 16 uncalibrated
Yellowstone, WY 0, 3, 10, 11, 18 f060925t01p00r12 2006 677 16 calibrated
Hawaii 1 f011020t01p03r05 2001 614 12 uncalibrated
Maine 10 f030828t01p00r05 2003 680 12 uncalibrated

Download (hyperspectral images in ZIP format):

For further information about AVIRIS, please visit the AVIRIS web site.

Hyperion Hyperspectral Images

These Hyperion Level 0 (raw, uncalibrated) images are provided by the EO-1 Mission, NASA/USGS. Each image has width 256 cross-track samples, 242 spectral channels, and the height indicated in the table below. The Hyperion imager produces 12-bit data samples. In the files here, each sample is stored as a 2-byte unsigned integer in little-endian byte order, samples arranged in BIP order. A false-color browse image is included with each image.

Site Date Image Height
Lake Monona June 15, 2009 EO1H0240302009166110PF: EO12009166_48AD48AC_r1_SGS_01.L0 3176
Mt. St. Helens August 19, 2009 EO1H0460282009231110KF: EO12009231_7FED7FEC_r1_PF2_01.L0 3242
Erta Ale February 26, 2010 EO1H1680502010057110KF: EO12010057_7F2D7F2C_r1_PF2_01.L0 3187

Download (hyperspectral images in ZIP format):

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