Exploiting Calibration-Induced Artifacts in Lossless Compression of Hyperspectral Imagery

Kiely, Aaron; Klimesh, M.

doi:10.1109/tgrs.2009.2015291

Cited by 78 publications

(45 citation statements)

References 17 publications

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“…LUT based algorithms have been shown to achieve 15-20% reduced compression ratio on uncalibrated data when compared to calibrated data performance. As calibration processes are performed on the ground, as post-processing, the LUT compression performance for raw uncalibrated onboard data is expected to be significantly less than alternative predictive based schemes [9].…”

Section: Lossless Image Compression Literature Reviewmentioning

confidence: 99%

Adaptive multispectral GPU accelerated architecture for Earth Observation satellites

Davidson

Bridges

2016

2016 IEEE International Conference on Imaging Systems and Techniques (IST)

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Abstract-In recent years the growth in quantity, diversity and capability of Earth Observation (EO) satellites, has enabled increase's in the achievable payload data dimensionality and volume. However, the lack of equivalent advancement in downlink technology has resulted in the development of an onboard data bottleneck. This bottleneck must be alleviated in order for EO satellites to continue to efficiently provide high quality and increasing quantities of payload data.This research explores the selection and implementation of state-of-the-art multidimensional image compression algorithms and proposes a new onboard data processing architecture, to help alleviate the bottleneck and increase the data throughput of the platform. The proposed new system is based upon a backplane architecture to provide scalability with different satellite platform sizes and varying mission's objectives. The heterogeneous nature of the architecture allows benefits of both Field Programmable Gate Array (FPGA) and Graphical Processing Unit (GPU) hardware to be leveraged for maximised data processing throughput.

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Section: Lossless Image Compression Literature Reviewmentioning

confidence: 99%

Adaptive multispectral GPU accelerated architecture for Earth Observation satellites

Davidson

Bridges

2016

2016 IEEE International Conference on Imaging Systems and Techniques (IST)

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“…Each image is composed of 224 bands and each scene (the scene numbers are 0, 3, 10, 11, 18) has 512 lines. 7 All data have been clipped to 14 bits (a negligible percentage of outliers has been affected by clipping) and remapped to 12 bits to simulate a space-borne instrument, e.g., Hyperion. Figure 6 portrays a sample band (#20, wavelength between green and red).…”

Section: Aviris 2006 Datamentioning

confidence: 99%

Information-theoretic assessment of on-board near-lossless compression of hyperspectral data

Aiazzi

Alparone

Baronti

et al. 2013

J. Appl. Remote Sens

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Abstract.A rate-distortion model to measure the impact of near-lossless compression of raw data, that is, compression with user-defined maximum absolute error, on the information available once the compressed data have been received and decompressed is proposed. Such a model requires the original uncompressed raw data and their measured noise variances. Advanced nearlossless methods are exploited only to measure the entropy of the datasets but are not required for on-board compression. In substance, the acquired raw data are regarded as a noisy realization of a noise-free spectral information source. The useful spectral information at the decoder is the mutual information between the unknown ideal source and the decoded source, which is affected by both instrument noise and compression-induced distortion. Experiments on simulated noisy images, in which the noise-free source and the noise realization are exactly known, show the trend of spectral information versus compression distortion, which in turn is related to the coded bit rate or equivalently to the compression ratio through the rate-distortion characteristic of the encoder used on satellite. Preliminary experiments on airborne visible infrared imaging spectrometer (AVIRIS) 2006 Yellowstone sequences match the trends of the simulations. The main conclusion that can be drawn is that the noisier the dataset, the lower the CR that can be tolerated, in order to save a prefixed amount of spectral information. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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“…What immediately stands out is that the noise standard deviation distribution with the wavelength roughly follows the trend of a typical spectral irradiance of the sun, unlike the raw data where this effect does not occur. The explanation is that spectral dampers aimed at flattening the spectral response of the sun are built up within the instrument in order to avoid saturation of the 14-bit ADC [9]. Hence, not only the noise, but also the signal is spectrally constant in raw data.…”

Section: Virtually Lossless Compression Of Radiance Datamentioning

confidence: 99%

“…Lossless compression thoroughly preserves the information of the data but allows a moderate decrement in transmission bit rate to be achieved. Compression ratios attained even by the most advanced schemes are lower than three, with respect to PCM coding of raw data [7][8][9]. Thus, the bottleneck of downlink to ground stations may severely hamper the coverage capabilities of modern satellite instruments.…”

Section: Introductionmentioning

confidence: 99%

Spectral Distortion in Lossy Compression of Hyperspectral Data

Aiazzi

Alparone

Baronti

et al. 2012

Journal of Electrical and Computer Engineering

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Distortion allocation varying with wavelength in lossy compression of hyperspectral imagery is investigated, with the aim of minimizing the spectral distortion between original and decompressed data. The absolute angular error, or spectral angle mapper (SAM), is used to quantify spectral distortion, while radiometric distortions are measured by maximum absolute deviation (MAD) for near-lossless methods, for example, differential pulse code modulation (DPCM), or mean-squared error (MSE) for lossy methods, for example, spectral decorrelation followed by JPEG 2000. Two strategies of interband distortion allocation are compared: given a target average bit rate, distortion may be set to be constant with wavelength. Otherwise, it may be allocated proportionally to the noise level of each band, according to the virtually lossless protocol. Comparisons with the uncompressed originals show that the average SAM of radiance spectra is minimized by constant distortion allocation to radiance data. However, variable distortion allocation according to the virtually lossless protocol yields significantly lower SAM in case of reflectance spectra obtained from compressed radiance data, if compared with the constant distortion allocation at the same compression ratio.

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Exploiting Calibration-Induced Artifacts in Lossless Compression of Hyperspectral Imagery

Cited by 78 publications

References 17 publications

Adaptive multispectral GPU accelerated architecture for Earth Observation satellites

Adaptive multispectral GPU accelerated architecture for Earth Observation satellites

Information-theoretic assessment of on-board near-lossless compression of hyperspectral data

Spectral Distortion in Lossy Compression of Hyperspectral Data

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