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RangeRectQuant compresses scientific raster data with accurate rectangular sums

By PulseAugur Editorial · [1 sources] ·

Researchers have developed RangeRectQuant, a novel method for compressing scientific raster data. This technique ensures that all rectangular sums within the data remain accurate, even when individual pixels are modified. RangeRectQuant achieves substantial storage savings by controlling errors in prefix sums, allowing for efficient storage and arbitrary rectangular measurements without re-encoding or query-specific corrections. Experiments on geographic maps demonstrate its effectiveness over alternative methods. AI

IMPACT This method could enable more efficient storage and retrieval of large scientific datasets, potentially benefiting AI models that process such data.

RANK_REASON The cluster contains a single academic paper detailing a new compression technique for scientific data. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

RangeRectQuant compresses scientific raster data with accurate rectangular sums

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The cluster contains a single academic paper detailing a new compression technique for scientific data. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Jiahao Zhang, Xinling Wen, Yu Chen ·

    RangeRectQuant: Compressing Scientific Fields for Every Future Rectangular Sum

    arXiv:2610.36873v1 Announce Type: new Abstract: Scientific rasters are often stored before the regions to be measured are known. Independent pixel-error bounds can force exact integer reconstruction when one absolute error budget covers every future rectangle. Coordinated changes…

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