Abstract: Since the existing computational models of visual attention are not suitable to process data with dimensions higher than four,we introduce selective visual attention mechanism into target detection on multispectral imagery,and propose a visual attention computational approach based on biquaternion.By transforming multi-dimensional data into biquaternion and exploiting the phase spectrum of biquaternion Fourier transform（PBFT）,saliency map is generated for salient target detection.The original multi-dimensional data can be incorporated as a whole,and features both in spatial and frequency domain can be extracted effectively.Compared with traditional multispectral target detection methods,our method has very low computational complexity and is not sensitive to parameter setting.Experimental results on simulated and real multispectral remote sensing data show that the proposed method has excellent performance in ship detection and is robust against white noise.