Applicability of Hadamard relaxation method to MMW and THz Imaging with compressive sensing

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• 作者：Hao Tu ; Weihua Bu ; Wenjing Wang ; Bingxi Gao ; Hui Feng…
• 关键词：Hadamard relaxation method ; Millimeter wave and terahertz imaging ; Compressive sensing ; Tolerance to noise ; Efficiency
• 刊名：Signal, Image and Video Processing
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：11
• 期：3
• 页码：399-406
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Signal,Image and Speech Processing; Image Processing and Computer Vision; Computer Imaging, Vision, Pattern Recognition and Graphics; Multimedia Information Systems;
• 出版者：Springer London
• ISSN：1863-1711
• 卷排序：11

文摘

Compressive sensing (CS) is widely considered a promising method for millimeter wave (MMW) and terahertz (THz) imaging, especially in security screening. In many real-life application scenarios, a CS reconstruction algorithm has to be simultaneously robust, noise-tolerant and fast to be of practical use. However, a lot of CS reconstruction algorithms are not designed aiming at such overall performance, preventing them to become applicable in commercial imaging systems. Having investigated some CS algorithms, we find that Hadamard relaxation method is a potential candidate for commercial CS imaging. By using MATLAB, we study Hadamard relaxation method focusing on its under-sampling ratio, tolerance to noise and efficiency. Comparisons with several other CS algorithms are made using the available data in references. The results demonstrate that the overall performance of Hadamard relaxation method is among the best for real-life and real-time applications of MMW and THz imaging.