Abstract: Data processing services for Meteosat geostationary satellite are presented. Implemented services correspond to the different levels of remote-sensing data processing, including noise reduction at preprocessing level, cloud mask extraction at low-level and fractal dimension estimation at high-level. Cloud mask obtained as a result of Markovian segmentation of infrared data. To overcome high computation complexity of Markovian segmentation parallel algorithm is developed. Fractal dimension of Meteosat data estimated using fractional Brownian motion models.

Keywords: cloud mask, fractals, Meteosat, Markov Random Fields, fractional Brownian motion, parallel programming, MPI.

ACM Classification Keywords: I.4.6 Image Processing and Computer Vision: Segmentation – Pixel classification, G.1.2 Numerical Analysis: Approximation – Wavelets and fractals, D.1.3 Programming Techniques: Concurrent Programming – Parallel programming, I.4.7 Image Processing and Computer Vision: Feature Measurement – Texture

Link:

SERVICES FOR SATELLITE DATA PROCESSING

Andriy Shelestov, Oleksiy Kravchenko, Michael Korbakov

http://www.foibg.com/ijita/vol12/ijita12-3-p11.pdf