Optimization restoration algorithm for infrared object turbulencedegraded image

A blind restoration algorithm for turbulencedegraded image based on the steepest descent method is proposed. An objective function based on frequency spectrums of the object image and the pointspread function (PSF) is set up in the frequency domain, which is minimized by the steepest descent method in an iterative manner. FFT and IFFT are used to transfer the object image and the PSF between frequency domain and time domain, and the constraints of the frequency domain and space domain are introduced in each iteration to modify them, so as to obtain the expected image restoration effect, the proposed algorithm robustness and better immunity to noise. A series of restoration experiments for infrared object turbulencedegraded images are performed to test the proposed algorithm in the microcomputer, and the experimental results show that the proposed algorithm is robust and immune to noise.