CAJ | 학술논문

基于压缩感知理论，针对复信号的多通道成像处理提出了一种联合多通道稀疏表征的成像算法，可以应用于多通道或者多频段太赫兹成像中。在该算法中，通过对多通道复信号的幅度和相位分别进行联合稀疏约束，将成像模型转换为求解正则化最优化问题。相比于单个通道独立处理，该算法能够有效保护多通道之间的信息，同时具有较好的噪声抑制能力。基于仿真数据的实验验证了本文分析的可行性和合理性。
기우압축감지이론，침대복신호적다통도성상처리제출료일충연합다통도희소표정적성상산법，가이응용우다통도혹자다빈단태혁자성상중。재해산법중，통과대다통도복신호적폭도화상위분별진행연합희소약속，장성상모형전환위구해정칙화최우화문제。상비우단개통도독립처리，해산법능구유효보호다통도지간적신식，동시구유교호적조성억제능력。기우방진수거적실험험증료본문분석적가행성화합이성。
From compressive sensing theory,we propose a novel method of joint complex-data sparse representation for multichannel imaging,which can be applied in terahertz(THz)imaging.In the scheme, the imaging model is transformed into an optimization by enforcing joint sparsity constraints on both magnitude and phase combining different channel data.In comparison of independent single channel imaging, the proposed algorithm takes the advantages of preserving cross-channel information and denoising.The experiments based on simulated data confirm the validation the proposal.