无源毫米波成像最大似然频域校正超分辨算法

在无源毫米波成像中, 因为天线孔径大小的限制而导致获取的图像分辨率低, 所以必须采取有效的后处理措施增强分辨率. 本文提出了一种针对无源毫米波成像应用的最大似然频域校正超分辨算法. 该算法首先使用Wiener滤波复原算法恢复图像通带内的频谱分量, 然后运用Richardson-Lucy算法实现频谱外推, 最后通过一种频域校正算法, 用Wiener滤波器恢复的频谱代替通带内的频谱, 保证图像的低频分量不被破坏. 实验结果表明, 该算法改善了收敛速度, 增强了图像的分辨率, 同时能够有效地减轻恢复图像中的振铃波纹, 有利于无源毫米波成像超分辨的实现.

Maximum Likelihood Frequency Domain Correction Super-resolution Algorithm for Passive Millimeter Wave Imaging

The problem of poor resolution of acquired image in the passive millimeter wave imaging stems mainly from antenna size limitations, thus necessitating some efficient post-processing to achieve resolution improvements. A maximum likelihood (ML) super-resolution algorithm based on frequency domain correction is proposed. First, we employ Wiener filter to restore passband spectrum, then we implement Richardson-Lucy algorithm to complete spectral extrapolation, lastly we implement a spatial spectrum correction algorithm in which the calculated spectrum within the passband is replaced by the low frequency component restored by Wiener filter. Experimental results demonstrate the algorithm improves the convergent rate and enhances the resolution and reduces the ringing effects which are caused by regularizing the image restoration problem. Furthermore, the algorithm is easily implemented for passive millimeter wave imaging.