Abstract: Two-dimensional FFT is a typical algorithm of image processing, widely used in image filtering, fast convolution, target tracking and other fields. A parallel implementation method of 2D FFT algorithm based on the self-developed FT-X many-core DSP is proposed, in order to meet the real-time processing requirements of high resolution images. Based on the multi-core programming model, the task initialization is accomplished through multi-core task deployment and address space remapping. The parallel data processing of 24 cores is realized and the speed ratio is 19.8 times. An implicit transpose based on DMA step transfer is proposed, which uses matrix address allocation to solve the problem of limited step size in large matrix step transfer. Experimental results show that compared with direct transpose and instruction implicit transpose, the transpose time is saved 91% and 65% respectively at 8K×8K data scale. At the same time, the problem of unbalanced multi-core load in a special case is identified and solved. The difference between cores fell from 64% to 12%, and overall time fell 26%.