To solve the problem that the resolution of the millimeter-wave passive imaging is low, a new effective super-resolution algorithm is proposed. Wiener filtering algorithm is improved, and the low-frequency components are restored. The low-frequency components of instead of the pass-band with spectrum component is put to making full use of the information in the image and make it self-adaptive. Then the adaptive Wiener filtering and regular maximum a posteriori (MAP) super-resolution algorithm which can extrapolate high-frequency component are combined. The regular MAP iterative algorithm is used to obtain extrapolated high-frequency components, the frequency domain correction is conducted for Fourier transform of the image, and inverse transform of the image is carried out for further correction, the above process is performed successesively until the resolution of the image is improved. The new adaptive super-resolution algorithm is tested through the simulation experiments. The simulation results show that the new algorithm can enhance the resolution, improve the peak value signal-to-noise ratio and has fast convergence. The visual effect is superior to the other two algorithms; which indicate that the new algorithm is effective.