Multi-temporal high-resolution remote sensing image building extraction method based on multi-feature LSTM network
A high-resolution, remote sensing image technology, applied in the field of satellite remote sensing image processing and application, can solve the problems of high misclassification rate, blurred border, low accuracy rate, etc.
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[0073] Using 6 photos taken on January 2, 2015, May 15, 2015, September 20, 2015, November 28, 2015, March 25, 2016 and February 28, 2017 (GF-2) Multi-temporal remote sensing images are used as the data source. After image preprocessing of 6 original data, the segmentation method combining HSI color transformation, image segmentation and conditional random field post-processing, Gabor wavelet transform and DSBI index calculation are used. The method extracts the building features of the multi-temporal data of 6 scenes, and finally arranges the extracted multi-temporal building feature bands and the four bands of the original data according to the order of the shooting time of the original satellite data to form a multi-temporal multi-temporal network with 60 bands. Phase building feature set, the feature set is used as the input data of the multi-feature LSTM network to train the multi-temporal building extraction model and obtain the rough extraction result of the building. Af...
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