Chao Wang

To simultaneously acquire the spectral and polarization information of the target and achieve the monitoring and identification of the target object, a polarization spectral integrated imaging system is proposed in this paper. Firstly, the structural principle of the polarization spectral integrated imaging system is introduced. The relationship between the spatial resolution, spectral resolution, and the system’s structural parameters is analyzed. The design of the optical part of the polarization spectral integrated imaging system is completed, along with the tolerance analysis. Secondly, the mechanical structure of the polarization spectral integrated imaging system is designed. Finally, by using a drone to carry the polarization spectral integrated imaging system, a simulation experiment for sea surface oil spill monitoring is conducted, and the hyperspectral and polarization information of the ocean, crude oil, fuel oil, palm oil, diesel, and gasoline are obtained. The polarization and spectral information were integrated. The integration of hyperspectral and polarization data yields remarkable enhancement outcomes, allowing for the clear delineation of previously challenging-to-identify crude oil contamination areas against the marine background in the fused images, characterized by sharper boundaries and improved discriminability. This accomplishment underscores the feasibility of our system for the rapid identification of large-scale oil spill events.

To address the problem of slit limitation in traditional slit imaging spectrometers, which hampers fast the identification, efficient tracking, and precise avoidance of faint targets in lunar orbit, this article proposes a lenslet-array integral field spectrometer structure that is free of slits, static, and that is fast and efficient for the visible-to-near-infrared wavelength band. Firstly, the field of view segmentation model is analyzed, and the requirement of the telecentric degree of the pre-imaging system is obtained. Secondly, the influence of aberrations, such as spherical aberration and coma distortion on the micro-pupil dispersion model is analyzed. Based on this, the pre-imaging system is designed to meet the requirements of aberration correction and the telecentricity of the system. Finally, the structure of the spectral system is designed, and the integrated system is optimized. The smile of the lenslet-array integral field spectrometer is ±1 nm, and the MTF is greater than 0.7 at 60 lp/mm and close to the diffraction limit.

Infrared small-target enhancement in complex contexts is one of the key technologies for infrared search and tracking systems. The effect of enhancement directly determines the reliability of the monitoring equipment. To address the problem of the low signal-to-noise ratio of small infrared moving targets in complex backgrounds and the poor effect of traditional enhancement algorithms, an accurate enhancement method for small infrared moving targets based on two-channel information is proposed. For a single frame, a modified curvature filter is used in the A channel to weaken the background while an improved PM model is used to enhance the target, and a modified band-pass filter is used in the B channel for coarse enhancement followed by a local contrast algorithm for fine enhancement, based on which a weighted superposition algorithm is used to extract a single-frame candidate target. The results of the experimental data analysis prove that the method has a good enhancement effect and robustness for small IR motion target enhancement in complex backgrounds, and it outperforms other advanced algorithms by about 43.7% in ROC.

In order to meet the high accuracy pixel-matching requirements of space-dimensional dual-coded spectropolarimeter, a dual-coded image pixel-matching method based on dispersion modulation is proposed. The mathematics of the dispersion power and the pixel matching is modeled. The relationship between different pixel-matching coefficients and the peak signal-to-noise ratio (PSNR) and structure similarity index measure (SSIM) of reconstructed images is analyzed. An imaging system experiment consisting of a digital micromirror device (DMD), a micro-polarizer array detector (MPA), and a prism–grating–prism (PGP) is built to reconstruct a spectral linear polarization data cube with 50 spectral channels and linear polarization parameters. The contrast ratio of the reconstructed spectropolarimeter image was raised 68 times against the ground truth. It can be seen from the reconstruction evaluation analysis that the spectral data and polarization data can be matched effectively by optimizing the dispersion coefficient of the PGP. The system can effectively reconstruct when the noise SNR is greater than 15 dB. The PSNR and SSIM of the reconstruction images can be improved by increasing the pixel-matching spacing. The optimal choice of the dual-coded pixel-matching spacing is one super-polarized pixel. The spectral resolution and quality of the spectropolarimeter are improved using the pixel-matching method.

In the field of compressed imaging, many attempts have been made to use the high-resolution digital micromirror array (DMD) in combination with low-resolution detectors to construct imaging systems by collecting low-resolution compressed data to reconstruct high-resolution images. However, the difficulty of achieving micrometer-level alignment between DMD devices and detectors has resulted in significant reconstruction errors. To address this issue, we proposed a joint input generative adversarial network with an error correction function that simulates the degradation of image quality due to alignment errors, designed an optical imaging system, and incorporated prior imaging system knowledge in the data generation process to improve the training efficiency and reconstruction performance. Our network achieved the ability to reconstruct 4× high-resolution images with different alignment errors and performed outstanding reconstruction in real-world scenes. Compared to existing algorithms, our method had a higher peak signal-to-noise ratio (PSNR) and better visualization results, which demonstrates the feasibility of our approach.

Complex illumination, solar flares and heavy smog on the sea surface have caused difficulties to accurately obtain high-quality imaging and multi-dimensional information of marine monitoring targets, such as oil spill, red tide and underwater vehicle wake. The principle of existing imaging mechanism is complex, and thus it is not practical to capture high-resolution infrared images efficiently. To combat this challenge by utilizing new infrared optical materials and single point diamond-turning technology, we designed and processed a simple, light and strong condensing ability medium and long wavelength infrared imaging optical system with large relative aperture, which can obtain high-quality infrared images. On top of this, with the training from a combination of infrared and visible light images, we also proposed a super-resolution network model, which is composed of a feature extraction layer, an information extraction block and a reconstruction block. The initial features of the input images are recognized in feature extraction layer. Next, to supply missing feature information and recover more details on infrared image extracted from a dense connection block, a feature mapping attention mechanism is introduced. Its main function is to transfer the important feature information of the visible light images in the information extraction block. Finally, the global feature information is integrated in the reconstruction block to reconstruct the high-resolution infrared image. We experimented our algorithm on both of the public Kaist datasets and self-collected datasets, and then compared it with several relevant algorithms. The results showed that our algorithm can significantly improve the reconstruction performance and reveal more detail information, and enhance the visual effect. Therefore, it brings excellent potential in dealing with the problem of low resolution of optical infrared imaging in complex marine environment.