This invention discloses an intelligence generation method and
system based on feature
fingerprint storage and spatiotemporal geometric correction, belonging to the field of intelligent
remote sensing image processing technology. The method involves: accessing heterogeneous data streams generated from multi-source
remote sensing images in a synchronized
time sequence; inputting a shared
backbone network and a modality
adaptation layer to generate a current feature
stream in a unified
semantic space; asynchronously retrieving historical baseline features from an in-memory feature
fingerprint database based on geographic coordinates; fusing
satellite imaging parameters with the current feature
stream and inputting it into a
spatial transformation network,
resampling historical baseline features using a regression
transformation matrix to achieve spatiotemporal geometric correction in the feature domain; weighted fusing of the current feature streams from each modality to generate a fused feature
stream; and parallel interpretation and semantic encapsulation of the fused feature stream to generate a
natural language intelligence report. This invention reduces memory usage and data
throughput, shortens the intelligence generation cycle, reduces the
false alarm rate, and achieves synergistic optimization of timeliness, accuracy, and
automation.