NSST domain sonar image fusion combining PCNN and local energy

Aiming at the problems of local feature blur and edge information loss of sonar image, a sonar image fusion method in non-subsampled shearlet domain is proposed, which combines parameter adaptive pulse coupled neural network and improved local energy fusion rules. The non-subsampled shearlet transform is used to decompose multiple source images into high-frequency coefficients and low-frequency coefficients, and the parameter adaptive pulse coupled neural network is used to process the high-frequency coefficients to integrate image edge information. The traditional local energy fusion rule is improved and applied to the processing of low-frequency coefficients to retain most of the original energy of the image. Finally, the processed high-frequency coefficients and low-frequency coefficients are reconstructed by the inverse transformation of non-subsampled shearlet to realize the fusion of sonar images. The simulation results show that this method can transfer the edge information and feature information in the source image to the fused image, and greatly improve the sonar image quality.