Abstract
The study of marine scenes has always been a relevant subject for environmental sciences and ocean engineering. In this contribution we have analyzed infrared imagery applied to surveillance of the sea surface. We present a method based on the principal component analysis to study infrared sea scenes separating the actual scene from spatial-temporal artifacts coming from the imagers. Besides the filtering capabilities, the method obtains spatial-temporal correlation functions and the power spectrum density of the original data set. A time scale associated with the noise of the imager is defined. Solar glints identification is also addressed. One relevant feature of this method is its automatic implementation.
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