The invention provides a real-time target detection method and
system based on motion trail prediction and calibration. According to the method, the multi-dimensional displacement vector is generated through the
motion measurement data, and the
reference frame with the lowest blurring in the
image sequence is screened according to the multi-dimensional displacement vector. And combining the displacement vector and the
reference frame to construct a motion track model, performing
motion blur reverse compensation on the current frame, generating a local clear image, and recording pixel displacement data. And performing
frequency domain decomposition on the clear image, and generating a fuzzy intensity
distribution diagram in combination with displacement data so as to adaptively reinforce the high-frequency edge. And meanwhile, fusing displacement data to predict a target trajectory, and generating a spatial offset weight matrix to restore a target geometric position. And finally, carrying out weighted fusion on the restored features and the enhanced edges, carrying out track consistency calibration by using a motion
calibration coefficient graph, and outputting an optimized feature graph for target detection. According to the invention, through dynamic trajectory modeling, fuzzy compensation,
edge enhancement and position restoration, the precision of real-time target detection in a motion fuzzy scene is significantly improved.