The invention provides a multi-
modal salient target detection method combining dynamic routing with multiple asymmetric windows, and belongs to the field of
image processing. The method comprises the following steps: S1,
processing visible light and
thermal infrared image pairs by using two parallel neural network branches to form visible light and
thermal infrared feature maps of each layer; s2, performing division by using windows with different sizes, and obtaining large feature maps and small feature maps of different
layers; s3, applying a dynamic path
selection strategy to acquire high-level features after weighted aggregation, acquiring global features and acquiring enhanced features of different
layers; s4, the aligned features of different
layers are obtained; and S5, combining the zeroth layer of the visible light and
thermal infrared feature map to obtain a predicted
saliency map. According to the method, features of different layers are dynamically selected and weighted, multi-size window modeling is carried out for correlation of different
modes of unaligned salient regions by utilizing a
visual attention mechanism, the problem that a
data set needs to be aligned in RGBT salient target detection is solved, and the prediction performance is excellent.