Abstract
In the research of passive millimetre wave (PMMW) imaging, the focal plane array (FPA) can realize fast, wide-range imaging and detection. However, it has suffered from a limited aperture and off-axis aberration. Thus, the result of FPA is usually blurred by space-variant point spread function (SVPSF) and is hard to restore. In this paper, a polar-coordinate point spread function (PCPSF) model is presented to describe the circle symmetric characteristic of space-variant blur, and a log-polar-coordinate transformation (LPCT) method is propagated as the pre-processing step before the Lucy–Richardson algorithm to eliminate the space variance of blur. Compared with the traditional image deblur method, LPCT solves the problem by analyzing the physical model instead of the approximating it, which has proved to be a feasible way to deblur the FPA imaging system.
Highlights
In the research of passive millimetre wave (PMMW) imaging, focal plane array (FPA) is widely applied for object detection, scene monitoring, and security checks, because of its fast and wide-range of imaging abilities
After analyzing the PSF of our system, we proposed the use of a log-polar-coordinate transformation (LPCT) method before the Lucy–Richardson algorithm to eliminate the space-variant blur in both the angular direction and the radial direction
Considering the requirements for imaging and locating the electromagnetic leakage of electronic equipment, here, we used the correctness of position and the number of radiation sources as the criteria for evaluating the super-resolution algorithm
Summary
In the research of passive millimetre wave (PMMW) imaging, focal plane array (FPA) is widely applied for object detection, scene monitoring, and security checks, because of its fast and wide-range of imaging abilities. The reflector of the PFPM system is offset to offset center obscuring, and its aperture is much larger than that in PMMW to match the microwave wavelengths according to diffraction theory.
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