Near lossless data compression onboard a hyperspectral satellite

Qian, Shen‐En; Bergeron, Martin; Cunningham, Ian; Gagnon, L. G.; Hollinger, A.

doi:10.1109/taes.2006.248183

Cited by 41 publications

(33 citation statements)

References 31 publications

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“…The compression distortion degree is generally set to less than 0.1% for engineering applications. A range of compression ratio of the telemetry data in the previous research is from 1.38 to 42 [9,19,20]. The data precision is larger than 8 bits.…”

Section: Introductionmentioning

confidence: 93%

“…Maluf et al combined discrete Fourier transforms (DFTs) with LZW and Flate algorithms for textual data and JPEG coding for images [8]. Two almost lossless data compression algorithms were proposed for the telemetry data produced by hyperspectral sensors installed on a satellite [9]. The telemetry video signals of the surface of Mars are compressed with a compression ratio of 24:1 and then transmitted from the Mars to the Earth by USA Mars Exploration Rovers [10].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Enhanced Run-Length Encoding Compression Method for Telemetry Data

Shan

Ren

Guo-yong

et al. 2017

Metrology and Measurement Systems

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The telemetry data are essential in evaluating the performance of aircraft and diagnosing its failures. This work combines the oversampling technology with the run-length encoding compression algorithm with an error factor to further enhance the compression performance of telemetry data in a multichannel acquisition system. Compression of telemetry data is carried out with the use of FPGAs. In the experiments there are used pulse signals and vibration signals. The proposed method is compared with two existing methods. The experimental results indicate that the compression ratio, precision, and distortion degree of the telemetry data are improved significantly compared with those obtained by the existing methods. The implementation and measurement of the proposed telemetry data compression method show its effectiveness when used in a high-precision high-capacity multichannel acquisition system.

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Section: Introductionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

An Enhanced Run-Length Encoding Compression Method for Telemetry Data

Shan

Ren

Guo-yong

et al. 2017

Metrology and Measurement Systems

View full text Add to dashboard Cite

show abstract

“…In [95], the author used the discrete Hartley transform (DHT). Vector quantization methods are presented in [87,88,92]. A DPCM is used in [4].…”

Section: Spectral Decorrelationmentioning

confidence: 99%

Reconfigurable architecture for real-time image compression on-board satellites

Manthey

Krutz

Juurlink

2015

J. Appl. Remote Sens

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Data products of optical remote sensing systems are increasingly used in many areas of our everyday life. The spatial as well as the spectral resolution of satellite image data increases steadily with new missions resulting in a higher precision of known procedures and new application scenarios. While the memory capacity requirements can still be fulfilled, the transmission capacity becomes increasingly problematic. Real-time transmission of high-resolution image data is currently not possible.This thesis presents a new image data compression architecture that can be used for current and future projects at the German Aerospace Center (DLR). The architecture has region-of-interest support and offers flexible access to the compressed data based on the CCSDS 122.0-B-1 image data compression standard. Region of interest (ROI) coding can be useful in scenarios where on-board classification, registration, or object or change detection algorithms are used. It is also useful to decrease the amount of data that must be transferred to the ground station. Modifications to the standard have been made to permit a change of compression parameters and the re-organization of the bit-stream after compression. An additional index of the compressed data is created, which makes it possible to locate individual parts of the bit-stream. On request, compressed and stored images can be re-assembled and transmitted according to the application's needs and as requested by the ground station.The requirements, the design of the architecture, and its implementation based on reconfigurable hardware are presented. The architecture was developed for a spacequalified Xilinx Virtex 5QV, where a single instance of the architecture is capable of compressing images at a rate of up to 200 Mpx /s (or 400 Mbyte /s for 16 bit images). It operates at a clock frequency of 100 MHz and processes two image pixels per clock cycle. A Xilinx Virtex-5QV enables thereby compressing images with a width of up to 4096 pixels without the use of external memory. Without external memory and additional interfaces, the power consumption of the architecture is about 5 W. The proposed architecture is one of the fastest implementations yet reported and sufficient for recent high-resolution systems. Investigations in the resource and power consumption, as well as the availability of external storage have shown that it should be possible to integrate the design directly on a focal plane.

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“…However, such statistical information may be mostly due to random fluctuations of the instrumental noise. The rationale that compression-induced distortion may be less harmful in those bands, in which the noise is higher, constitutes the virtually lossless paradigm, 14 which is accepted by several authors, 15 but has never been demonstrated. This paper faces the problem of quantifying the trade-off between compression ratio (CR) and decrement in the spectral information content.…”

Section: Introductionmentioning

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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Near lossless data compression onboard a hyperspectral satellite

Cited by 41 publications

References 31 publications

An Enhanced Run-Length Encoding Compression Method for Telemetry Data

An Enhanced Run-Length Encoding Compression Method for Telemetry Data

Reconfigurable architecture for real-time image compression on-board satellites

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

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