FINE WATER BODY EXTRACTION METHOD BASED ON U-NET NEURAL NETWORK

摘要

Disclosed is a fine water body extraction method based on a U-net neural network, which method relates to the technical field of convolutional neural networks and water body extraction, and particularly relates to water body extraction by means of hyperspectral data. The method comprises: importing original images of all wavebands into ENVI for principal component analysis; forming a variety of combinations of different principal components; forming label data; dividing an optimal remote-sensing image into training data and test data; inputting all the training data into a U-net neural network for training; inputting the test data of the optimal remote-sensing image into the trained U-net neural network, so as to obtain an output image; performing threshold value segmentation and splicing on the output image, and restoring the output image to an original size; and comparing the output image which has been restored to the original size with the test data in the label data, so as to evaluate the precision of fine water body extraction.