Towards Optimal Compression of Meteorological Data: A Case Study of Using Interval-Motivated Overestimators in Global Optimization

Olga Kosheleva ()
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Olga Kosheleva: University of Texas

A chapter in Models and Algorithms for Global Optimization, 2007, pp 59-71 from Springer

Abstract: Abstract The existing image and data compression techniques try to minimize the mean square deviation between the original data f(x, y, z) and the compressed-decompressed data f(x, y, z). In many practical situations, reconstruction that only guaranteed mean square error over the data set is unacceptable.

Keywords: Mean Square Error; Meteorological Data; Data Compression; JPEG2000 Compression; Interval Uncertainty (search for similar items in EconPapers)
Date: 2007
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DOI: 10.1007/978-0-387-36721-7_4

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