CAJ | 학술논문

针对无源毫米波成像中图像分辨率低的问题,提出了一种改进的最大后验(MAP)超分辨算法.该算法结合了Wiener滤波复原算法和基于泊松分布的MAP算法的优点,使用Wiener滤波复原算法恢复图像通带内的低频分量,运用MAP算法作为主迭代过程实现频谱外推,同时保证低频分量不被破坏;并对该算法的计算复杂度和实时性进行了分析.通过仿真可知,该算法可有效地恢复图像截止频谱外的信息,提高图像空间分辨率,处理时间少,易于实现并行处理.
침대무원호미파성상중도상분변솔저적문제,제출료일충개진적최대후험(MAP)초분변산법.해산법결합료Wiener려파복원산법화기우박송분포적MAP산법적우점,사용Wiener려파복원산법회복도상통대내적저빈분량,운용MAP산법작위주질대과정실현빈보외추,동시보증저빈분량불피파배;병대해산법적계산복잡도화실시성진행료분석.통과방진가지,해산법가유효지회복도상절지빈보외적신식,제고도상공간분변솔,처리시간소,역우실현병행처리.
To solve the problem of poor resolution in passive millimeter wave (PMMW) imaging, we present an improved maximum a posteriori (MAP) super-resolution algorithm. The algorithm combines the advantages of Wiener filter restoration algorithm and MAP algorithm based on Poisson distribution. The Wiener filter is employed to restore the pass-band spectrum, and the MAP algorithm is applied to complete spectral extrapolation as the main iterative process to ensure that low-frequency component is not destroyed as spectral extrapolating. Meanwhile, the computational complexity and real time of the algorithm are analyzed. Furthermore, simulation results show that the algorithm can effectively restore the frequency out side the cut off frequency, enhances the resolution and can be implemented by parallel processing.