Meteor automatic imager and analyzer: analysis of noise characteristics and possible noise suppression
Jan Švihlík, Karel Fliegel, Petr Páta, S. Vítek, Pavel Koten · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2010
This paper is devoted to the noise analysis and noise suppression in a system for double station observation of the meteors now known as MAIA (Meteor Automatic Imager and Analyzer). The noise analysis is based on acquisition of testing video sequences at different light conditions and their further analysis. The main goal is to find a suitable noise model and subsequently determine if the noise is signal dependent or not. Noise and image model in the wavelet domain should be based on Gaussian mixture model (GMM) or Generalized Laplacian Model (GLM) and the model parameters should be estimated by moment method. GMM and GLM allow to model various types of probability density functions. Finally the advanced de-noising algorithm using Bayesian estimator will be applied.