A neural network approach to cloud detection in AVHRR images

Document Type

Conference Proceeding

Date of Original Version



The problem of identifying clouds and fog areas from advanced very high resolution radiometer (AVHRR) images using a neural network approach is used. The backpropagation paradigm was used to train many different architectural configurations of the neural network to classify the cloud content of an 8 × 8-pixel window in an image into five categories (ranging from 100% cloudy to 0% cloudy). The results indicate a large range in the performance of the different architectures. The most successful architectural configuration was used to create cloud masks for a series of AVHRR images. The cloud masks generated compared favorably with a trained analyst and other automated techniques.

Publication Title, e.g., Journal

Proceedings. IJCNN-91-Seattle: International Joint Conference on Neural Networks

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