AERIAL FOGGY IMAGE REJECTION USing SINGLE NEURON
Aerial images taken during terrain mapping can be affected with a foggy weather. In this paper we proposed new fog
detection method and image rejection using single neuron. Fog detection is based on statistical data collected by
converting color image to grayscale image and then applying gamma correction factor. With this statistical data, training
dataset is created for single neuron. Neuron is simple two input neuron with sigmoid activation function. We establish
connection with single neuron and statistical data so it can recognize is there presence of fog in aerial image.
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