In this paper we show results of this processing chain for sea scenarios using our TNO turbulence mitigation method. Ship data is processed using the algorithm proposed above and the results are analyzed by both human observation and by image analysis. The improvement of the imagery is qualitatively shown by examining details which cannot be seen without processing and can be seen with processing. Quantitatively, the improvement is related to the energy per spatial frequency in the original and processed images and the signal to noise improvement. This provides a model for the improvement of the results, and is related to the improvement of the classification and identification range. The results show that with this novel approach the classification and identification range of ships is improved.
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