Detector MTF based micro-scanning image reconstruction

Detector MTF based micro-scanning image reconstruction (dMTF-MSIR) algorithm was presented to reduce image blur due to spatial integration degradation effect (SIDE) of focal plane detector. Firstly, a high-resolution oversampling image was generated from four successive frames in micro-scanning image sequence using inter-frame difference oversampling reconstruction (IFDOR) algorithm, in which case the required inherent inter-frame offsets were obtained by calibration. Secondly, a Wiener filter was built based on the SIDE model characterizing the image blur due to spatial integration of radiation intensity distribution at sensor cell surface. Finally, a high-resolution reconstructed image was generated by processing the oversampling image using the Wiener filter to reduce image blur due to SIDE. Simulation results showed that if spatial sampling frequency of focal plane detector was fixed and micro-scanning images were noise-free, the loss of reconstructed image detail increased with the increase of duty cycle of detector. However the influence of duty cycle of detector was gradually exceeded by that of image noise with the increase in image noise level, and in this case suppressing image noise should be given priority. Furthermore, the performance of the presented method was restricted by aliasing, so imaging light path should introduce an optical low-pass filter with the cutoff frequency that is less than or equal to twice as large as Nyquist sampling frequency of detector. The experiment based on infrared images of actual scene showed that reconstructed images generated by the presented method had a higher image contrast and sharpness than that of IFDOR algorithm.