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Optimizing ISOCAM data processing using spatial redundancy

Astrophysics · Submitted 7 Aug 2000

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim The data reduction corrects instrumental effects to the point where the noise in the final map is dominated by the readout and the photon noises.

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arXiv IDastro-ph/0008110 (version 1)
Pith IDBJQMO73D, Pith's permanent record of this paper and its review
CitationA. Abergel, F. Boulanger, J.-P. Bernard, M.-A. Miville-Deschenes. "Optimizing ISOCAM data processing using spatial redundancy." arXiv:astro-ph/0008110 (2000). https://pith.science/paper/BJQMO73D
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What the abstract itself states, as probabilities: claims first 0.06 · states limitation 0.32 · human participants 0.02 · controlled comparison 0.04 · randomized assignment 0.01 · states quantitative result 0.95 · compares with prior results 0.12 · mentions code or data availability 0.03.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

We present new data processing techniques that allow to correct the main instrumental effects that degrade the images obtained by ISOCAM, the camera on board the Infrared Space Observatory (ISO). Our techniques take advantage of the fact that a position on the sky has been observed by several pixels at different times. We use this information (1) to correct the long term variation of the detector response, (2) to correct memory effects after glitches and point sources, and (3) to refine the deglitching process. Our new method allows the detection of faint extended emission with contrast smaller than 1% of the zodiacal background. The data reduction corrects instrumental effects to the point where the noise in the final map is dominated by the readout and the photon noises. All raster ISOCAM observations can benefit from the data processing described here. These techniques could also be applied to other raster type observations (e.g. ISOPHOT or IRAC on SIRTF).

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 We present new data processing techniques that allow to correct the main instrumental effects that degrade the images obtained by ISOCAM, the camera on board the Infrared Space Observatory (ISO). contribution 1.00 0.91 0.19 asserted 1.00
s1 Our techniques take advantage of the fact that a position on the sky has been observed by several pixels at different times. method 0.98 0.33 0.04 asserted 1.00
s2 We use this information (1) to correct the long term variation of the detector response, (2) to correct memory effects after glitches and point sources, and (3) to refine the deglitching process. method 0.97 0.89 0.09 asserted 1.00
s3 Our new method allows the detection of faint extended emission with contrast smaller than 1% of the zodiacal background. result 0.98 0.90 0.32 asserted 0.97
s4 The data reduction corrects instrumental effects to the point where the noise in the final map is dominated by the readout and the photon noises. result 0.96 0.90 0.29 asserted 1.00
s5 All raster ISOCAM observations can benefit from the data processing described here. interpretation 0.72 0.31 0.16 asserted 0.99
s6 These techniques could also be applied to other raster type observations (e.g. ISOPHOT or IRAC on SIRTF). future work 0.73 0.11 0.07 hedged possibility 1.00

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from analysis of existing data 0.95.

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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

We present new data processing techniques that allow to correct the main instrumental effects that degrade the images obtained by ISOCAM, the camera on board the Infrared Space Observatory (ISO). Our techniques take advantage of the fact that a position on the sky has been observed by several pixels at different times. We use this information (1) to correct the long term variation of the detector response, (2) to correct memory effects after glitches and point sources, and (3) to refine the deglitching process. Our new method allows the detection of faint extended emission with contrast smaller than 1% of the zodiacal background. The data reduction corrects instrumental effects to the point where the noise in the final map is dominated by the readout and the photon noises. All raster ISOCAM observations can benefit from the data processing described here. These techniques could also be applied to other raster type observations (e.g. ISOPHOT or IRAC on SIRTF).

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