摘要
在无源毫米波成像中,由于系统天线孔径大小的受限而使得成像的分辨率低。为了提高图像的分辨率,该文提出了一种投影小波域最大后验(MAP)估计毫米波图像超分辨算法(PWMAP)。该算法利用基于小波域广义高斯分布的MAP估计来恢复通带内的频谱;然后利用投影的非线性运算实现频谱外推。该算法不仅比以往的算法能提供更准确的先验建模,而且能在每步迭代时自适应地更新正则参数。实验结果验证了该算法的有效性。
In passive millimeter wave imaging,the problem of poor resolution of acquired image stems mainly from system antenna size limitations. In order to achieve resolution improvements,a Projected Wavelet-domain Maximum A Posteriori （PWMAP） estimation super-resolution algorithm is proposed in this paper. This algorithm restores the spectrum in the pass-band based on wavelet domain using the generalized Gaussian distribution and the MAP estimate; then extrapolate the spectrum by using the non-linear projection operation. This algorithm can not only provide a more accurate priori model than previous algorithms,but also updates the parameter adaptively at each iteration. Experimental results show the effectiveness and superiority of the algorithm.
出处
《电子与信息学报》
EI
CSCD
北大核心
2010年第4期889-893,共5页
Journal of Electronics & Information Technology
基金
国家自然科学基金(60776823)
电子科技大学校青年基金(JX0823)资助课题
关键词
无源毫米波成像
超分辨
小波域
自适应
非线性运算
Passive millimeter wave imaging
Super-resolution
Wavelet-domain
Adaptive method
Non-linear operation
