Algorithms for high-speed universal noiseless coding

Rice, R. F.; Yeh, Pen-Shu; Miller, Warner H.

doi:10.2514/6.1993-4541

Cited by 39 publications

(40 citation statements)

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“…To overcome this, a loss-less data compression algorithm was implemented. The compression scheme is based on Rice's adaptive coding algorithm (Rice, 1993). Normally, for particle data, this scheme results in compression in the order of 4 to 5.…”

Section: Onboard Data Reductionmentioning

confidence: 99%

The MEDUSA electron and ion spectrometer and the PIA ultraviolet photometers on Astrid-2

Norberg

Winningham

Lauche³

et al. 2001

Ann. Geophys.

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Abstract. The miniature electron and ion spectrometer MEDUSA on Astrid-2 consists of two "top-hat"-type spherical electrostatic analyzers, sharing a common top-hat. Fast energy sweeps (16 electron sweeps and 8 ion sweeps per second) allow for very high temporal resolution measurements of a two-dimensional slice of the particle distribution function. The energy range covered, is in the case of electrons, 4 eV to 22 keV and, in the case of ions, 2 eV to 12 keV. MEDUSA is mounted with its aperture close to the spin plane of Astrid-2, which allows for good pitch-angle coverage when the local magnetic field is in the satellite spin plane. The PIA-1/2 spin-scanning ultraviolet photometers measure auroral emissions. Using the spacecraft spin and orbital motion, it is possible to create two-dimensional images from the data. Spin-scanning photometers, such as PIA, are low-cost, low mass alternatives to auroral imagers, but place constraints on the satellite attitude. Data from MEDUSA are used to study processes in the auroral region, in particular, electrodynamics of aurora and "black aurora". MEDUSA is also a technological development, paving the way for highly capable, miniaturized particle spectrometers.

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Section: Onboard Data Reductionmentioning

confidence: 99%

The MEDUSA electron and ion spectrometer and the PIA ultraviolet photometers on Astrid-2

Norberg

Winningham

Lauche³

et al. 2001

Ann. Geophys.

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show abstract

“…In the cases we have tested, the successive residual images from this decomposition have monotonically decreasing entropy, and appear to possess the stationarity properties that would make it possible for a single codebook to be adequate for all residual images. The final residual image and the VQ encoding indices from each level are losslessly compressed using either the Rice algorithm [10] or the Ziv-Lempel algorithm [11].…”

Section: Implementation Of Progressive Vqmentioning

confidence: 99%

Progressive vector quantization on a massively parallel SIMD machine with application to multispectral image data

Mareboyana

Tilton

1996

IEEE Trans. on Image Process.

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“…The residual image is obtained by taking the difference between the pixel values and their prediction values. The residual encoding primarily exploited Rice codes [12]. Two other forms of variable length coding were also evaluated.…”

Section: -Dimensional Adaptive Differential Pulse Coded Modulation (mentioning

confidence: 99%

“…A simple variable length code, the Rice code, and two other variable length codes based on Huffman codes are evaluated. Rice codes have been shown to be the optimum codes for the information sources with a geometric distribution [12]. They are also very simple to implement in hardware.…”

Section: Encoding Of Residualsmentioning

confidence: 99%

Lossless Predictive Compression of Hyperspectral Images

Wang

Sayood

Hyperspectral Data Compression

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Algorithms for high-speed universal noiseless coding

Cited by 39 publications

References 0 publications

The MEDUSA electron and ion spectrometer and the PIA ultraviolet photometers on Astrid-2

The MEDUSA electron and ion spectrometer and the PIA ultraviolet photometers on Astrid-2

Progressive vector quantization on a massively parallel SIMD machine with application to multispectral image data

Lossless Predictive Compression of Hyperspectral Images

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