To satisfy the requirement of real-time and rapid processing of Scale-Invariant Feature Transform(SIFT) algorithm for remote sensing images of large-scale Unmanned Aerial Vehicle (UAV) network on the scene, an implementation scheme of the algorithm by using the hardware multiplier of Digital Signal Processor(DSP)kernel was proposed to process the multiplication of single-precision floating-point pixel data. Firstly,according to the characteristics of data input and output of the hardware multiplier with DSP kernel,the image data structure and the image function of SIFT algorithm were reconstructed in order to make the hardware multiplier perform the multiplication calculation of single-precision floating-point pixel data of SIFT algorithm. Secondly,the software pipelining technology was adopted to rearrange the iterative computation,so as to enhance the parallel computing ability of the algorithm. Finally,the dynamic data produced in the algorithm calculation process were transferred to the Double Data Rate 3 synchronous dynamic random access memory(DDR3)to enlarge the storage space of the algorithm data. Experimental results show that the SIFT algorithm on DSP platform is able to achieve high-precision and fast processing for 1 000×750 remote sensing images of UAV,and the scheme satisfies the requirement of real-time and rapid processing of SIFT algorithm for remote sensing images of UAV network on the scene.