Spatiotemporal Fusion Algorithm of Remote Sensing Image Based on Single Example
Satellite images with high spatial resolution and high temporal resolution are important data for the study of land surface dynamics,and are widely used in monitoring land changes and disaster and estimating crop growth situation.However,due to technical limitations and other reasons,there are currently no sensors that can have both high-precision spatial resolution and frequent revisit cycles.Based on this,a spatio-temporal fusion method based on a single sample remote sensing image is proposed.Neural network is used to represent the mapping relationship between images with different spatial resolutions,so as to improve the accuracy of the model to predict the target image.From the experimental results,the proposed method has achieved good application effect.
remote sensing imagespace time fusionConvolutional Neural Networks(CNN)fine-rough image pair
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