Paper
19 September 2007 The impact of striping artifacts on compression
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Abstract
Despite tremendous efforts to avoid them, stripes are a re-occurring problem for many remote imaging sensors. Much work has focused on suppressing or eliminating them in order to recover accurate observed radiances. Beyond the obvious need to eliminate stripes to obtain accurate scientific measurements, stripes can also significantly impact the performance of compression algorithms. Many compression algorithms are based on linear representations of image space or assume the data to be relatively smooth. In contrast stripes produce nonlinearities in the data as well as sharp discontinuities which make it seem necessary to describe the images with many parameters. Yet the sources and nature of the stripes are often not well known, they could come from specific irregularities with the sensors. If the a priori construction of the sensor is accounted for, and the stripe statistically modeled, it is possible to transmit the stripe parameters separately along with de-striped images. The de-striped images have image statistics whose assumptions are much closer to those for which standard compression algorithms are optimized. As an example, we show this yields a significant boost in the performance of these algorithms when applied to the de-striped MODIS images.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael Grossberg, Srikanth Gottipati, and Irina Gladkova "The impact of striping artifacts on compression", Proc. SPIE 6683, Satellite Data Compression, Communications, and Archiving III, 66830L (19 September 2007); https://doi.org/10.1117/12.736585
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Sensors

Image compression

Image sensors

MODIS

Image processing

Calibration

Long wavelength infrared

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