Long-distance mid-wave infrared super-resolution compressive imaging. (January 2023)

• Record Type: Journal Article
• Authors: Jin, Xiao-Peng; Xiong, An-Dong; Wang, Xiao-Qing; Yao, Xu-Ri; Liu, Xue-Feng; Zhao, Qing
• Is Part Of: Optics & laser technology. Volume 157(2023)
• Publication Date: 2023-01
• Subjects: Compressive imaging -- Mid-wave infrared -- Super resolution -- Transfer function matrix -- Long distance; Optics -- Periodicals; Lasers -- Periodicals; Electronic journals; 621.366
• DOI: 10.1016/j.optlastec.2022.108740
• Languages: English
• ISSNs: 0030-3992

Abstract

Abstract: Super-resolution imaging (SRI) for mid-wave infrared (MWIR) has attracted increasing attention in recent years due to the expensive price for a large number of pixels MWIR cameras. Investigation of the compressed sensing method can partially improves the resolution. However, the quality of SRI is highly related to the transfer function matrix of the optical system, which is difficult to be accurately measured because of the noise existed in MWIR detection, especially in long-distance systems. In this work, we propose a transfer function matrix calculation method which overcomes the issues of low imaging contrast and signal-to-noise ratio compared with previous studies. And we further establish a long-distance focal plane array-based compressive imaging system with a resolution of two digital micro-mirror device pixels which just satisfies the system diffraction limit. In addition, we achieve the 4 × 4 times super-resolution high-quality reconstruction of long-distance digital and physical objects with only six measurements. Highlights: Establish a long-distance mid-wave infrared imaging system with high resolution. Calculate the transfer function matrix for 256 × 256 pixels with 100 random masks. Realize 4x4 times super-resolution reconstruction of digital or physical objects. Enhance the peak signal-to-noise ratio of 50% with only 6 measurements. Achieve the resolution of 2 pixels which fully utilizes the modulation resolution.