Target detection in remote sensing image based on saliency computation of spiking neural network

Target detection is a-priori conditions for target tracking, classification, recognition, and scene understanding in Remote Sensing Image (RSI) analysis. However, the many traditional algorithms for target detection cannot perform well when the image resolution, especially for high-resolution RSIs, is change. Therefore, in this paper, we introduce a novel target detection algorithm based on the visual saliency of Spiking Neural Networks (SNN), which can efficiently detect the discriminative information from high-resolution RSIs to find targets by a saliency computing. As a result of this, it can provide an efficient and fast calculation method. The proposed visual saliency algorithm was applied to extensive experiments to detect the ship, and experimental results showed the outstanding performance for target detection on the optical RSI and synthetic aperture image.