Paper
31 March 1982 Statistical Modeling Of Scene Variability
A. T. Maksymowicz, R. A. Bankus, W. W. Davis, V. J. Pecora, L. H. Wald
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Abstract
Temporal variations in a given background scene must be taken into account in evaluating the performance of infrared and microwave radiometric sensor systems. Some common examples are diurnal and seasonal temperature variations, changes in cloud patterns, precipitation and its accompanying effects on terrain, such as snow, ice, and water cover. As part of our Sensor Data Test Program, we propose to generate sets of simulated data frames chosen to be statistically representative of the temporal variations for particular background scenes. The simulation procedure utilizes parametric models of the changes in Question. Generation of the different simulated data frames is accomplished by varying the model parameters according to some specified statistical procedure. The present paper deals with the modeling of scene variations. In particular we describe our methodology for parametrizing the effects of scene variability by a statistical analysis of real data frames and present some examples of our results.
© (1982) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. T. Maksymowicz, R. A. Bankus, W. W. Davis, V. J. Pecora, and L. H. Wald "Statistical Modeling Of Scene Variability", Proc. SPIE 0304, Modern Utilization of Infrared Technology VII, (31 March 1982); https://doi.org/10.1117/12.932675
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KEYWORDS
Statistical analysis

Atmospheric modeling

Data modeling

Microwave radiation

Pollution control

Sensors

Monte Carlo methods

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