Most existing target detection algorithms for multi-spectral remotely sensed images dependent on the background model or prior knowledge of spectral

so the false alarm rate of detection algorithms would be enhanced by clutter background and little prior information.Inspired by small target detection neurons of the insect visual system

a bionic small target detection model and its corresponded detection method were proposed for multi-spectral remotely sensed images.Based on the nonlinear filtering characteristic of neural cell which is sensitive to transient signals

target detection was completed by suppressing the local background texture and enhancing target feature.Experimental results showed that the proposed method can detect target with stable low false alarm rate under the condition of complexity background.Meanwhile

the proposed method can balance the contradictory relationship between spatial resolution and background complexity.Compared with existing target detection algorithms

it was simple and easy to be completed.