Super-resolution Imaging System Research Articles

Bio-inspired foveal super-resolution method for multi-focal-length images based on local gradient constraints

Most existing super-resolution (SR) imaging systems, inspired by the bionic compound eye, utilize image registration and reconstruction algorithms to overcome the angular resolution limitations of individual imaging systems. This article introduces a multi-aperture multi-focal-length imaging system and a multi-focal-length image super-resolution algorithm, mimicking the foveal imaging of the human eye. Experimental results demonstrate that with the proposed imaging system and an SR imaging algorithm inspired by the human visual system, the proposed method can enhance the spatial resolution of the foveal region by up to 4 × compared to the original acquired image. These findings validate the effectiveness of the proposed imaging system and computational imaging algorithm in enhancing image texture and spatial resolution.

Joint constraints of guided filtering based confidence and nonlocal sparse tensor for color polarization super-resolution imaging.

This paper introduces a camera-array-based super-resolution color polarization imaging system designed to simultaneously capture color and polarization information of a scene in a single shot. Existing snapshot color polarization imaging has a complex structure and limited generalizability, which are overcome by the proposed system. In addition, a novel reconstruction algorithm is designed to exploit the complementarity and correlation between the twelve channels in acquired color polarization images for simultaneous super-resolution (SR) imaging and denoising. We propose a confidence-guided SR reconstruction algorithm based on guided filtering to enhance the constraint capability of the observed data. Additionally, by introducing adaptive parameters, we effectively balance the data fidelity constraint and the regularization constraint of nonlocal sparse tensor. Simulations were conducted to compare the proposed system with a color polarization camera. The results show that color polarization images generated by the proposed system and algorithm outperform those obtained from the color polarization camera and the state-of-the-art color polarization demosaicking algorithms. Moreover, the proposed algorithm also outperforms state-of-the-art SR algorithms based on deep learning. To evaluate the applicability of the proposed imaging system and reconstruction algorithm in practice, a prototype was constructed for color polarization image acquisition. Compared with conventional acquisition, the proposed solution demonstrates a significant improvement in the reconstructed color polarization images.

Super-resolution lensless imaging system based on a fast anti-diffraction algorithm.

Conventional lens imaging systems modulate incident rays with a set of lenses and focus these rays on their imaging planes. A lensless imaging system uses a single mask instead of lenses to project incident rays onto the imaging plane. These rays pass through or are blocked off according to the binary mask pattern. These systems are thin, lightweight, and inexpensive. However, they do not converge the rays, causing the local images corresponding to individual light transmission units to heavily overlap in a global scene, requiring a specific algorithm for decoding. Additionally, diffraction is unavoidable when the holes on the mask are extremely small, which can degrade the imaging quality. To address these difficulties, we propose a decoding algorithm called Fourier-ADMM algorithm to unwrap the overlapped images rapidly. In addition to providing high decoding speed, the proposed technique can suppress the diffraction from the tiny holes, owing to its conjugated structure. Based on this novel decoding algorithm, a lensless imaging system is proposed, which can handle overlapped and diffracted images with a single random mask. The camera can work beyond the theoretical diffraction limit and tremendously enhance the resolution. In summary, the super-resolution lensless camera provides users with additional options to suit different situations. It can facilitate robust, high-resolution, fast decoding without sophisticated calibration.

Comparative Analysis of Security Features in Banknotes Across Various Global Economies using VSC®-8000/HS

Background: Banknote counterfeiting is a serious issue. Every government adds various security elements to its banknotes to avoid forgery. The security measures inducted in the banknotes reduce the likelihood of counterfeiting. These are the unique elements that are incorporated during the production process. Paper quality, intaglio printing, watermarks, security threads, latent images, etc. are some of these unique properties. Every nation has a unique set of security characteristics. In the year 2016 India demonetized and recalled all of its highest denomination bank notes (Rs. 1000 and Rs. 500) in order to cease counterfeiting. Thereafter, there has been incorporation of various security features in the current Mahatma Gandhi series to make the currency standout with other international currencies, in order to reduce the chances of forgery as per the sections 489A-489E of Indian Penal Code, 1872. Methods: Banknote samples were analyzed using the non-destructive Video Spectral Comparator 8000 (VSC®-8000/HS) by foster+freeman®. Each sample was placed in the live-camera unit with high- resolution 12-megapixel camera forming the part of Super Resolution Imaging (SRI) system. Front and back pictures of the banknotes were taken in white light. The samples were then examined under various illumination settings (Spot Light, Oblique Light, Transmitted Light, UV-light, and Infrared light) for both sides. Security features like Microprinting, Micro texting, Guilloche Pattern, OVI, Watermarks, etc., were studied. Results: In the current research paper, the security characteristics of the banknotes of ten different countries are compared utilizing VSC®-8000/HS. Analysis reveals Thai Baht with the most security features, followed by Vietnamese Dong, Czech Koruna, Indian Rupees, and others. Notably, Indian banknotes stand out due to UV features, security thread, latent image, and strategic micro text placement. Conclusions: This research paper recognizes the importance of security features in various banknotes including the Indian banknotes and also provides some of the recommendations to enhance the quality and security features in the Indian banknotes.

Super-resolution macroscopic imaging via unknown speckle illumination using sparse aperture transmitter

Optical sparse aperture imaging technology has promising applications in the next generation of high-resolution imaging systems, but the phasing errors correction of sparse aperture is an urgent problem to be addressed. In this paper, we propose a blind structured-illumination super-resolution imaging system using a sparse aperture as the transmitter to overcome phasing errors and obtain higher resolution. In our scheme, an unknown pattern is projected onto the object by a sparse aperture system. By translating the unknown pattern, a sequence of modulated raw images is obtained. Based on these low-resolution raw images, the super-resolution object and the unknown illumination pattern are jointly estimated by the Adam algorithm. Here we show, both in the simulation and experiment, the resolution of reconstructions using sparse aperture as transmitter are similar to those using monolithic lens. Furthermore, we validate that the proposed method can protect the reconstruction effect from piston error and widen the tolerance range of tip/tilt error (peak-valley values) up to 0.5λ. At the same time, our proposed system can also alleviate to some extent the problem of mid-frequency modulation transfer function (MTF) attenuation that exists in sparse aperture imaging. Our approach not only simplifies the process of constructing synthetic aperture system, but also provides a novel application for synthetic aperture systems.

Super-resolution imaging system developed from vector superoscillatory field illumination.

Superoscillations are oscillations of a band limited waveform with a local frequency higher than the bandlimit. Spatial superoscillations show great potential for performing super-resolution imaging. However, these superoscillatory waveforms are inevitably surrounded by high intensity sidelobes which severely limit the usable super-resolved area of an image. In this study, we demonstrate how polarization engineering can be used in some circumstances to suppress superoscillation sidelobes, taking advantage of the transverse wave nature of light. We illustrate the principle by a model super-resolution imaging system that can image Rayleigh scatterers with separations smaller than the classic Rayleigh criterion.

Local super-resolution imaging of foveated areas in super-oscillating optical fields.

Herein, we propose a super-oscillation optical field foveated local super-resolution imaging method. Firstly, the post-diffraction integral equation of the foveated modulation device is constructed, the objective function and constraints are established, and the structural parameters of the amplitude modulation device are optimally solved by using genetic algorithm. Secondly, the solved data have been input into the software for point diffusion function analysis. We have studied the super-resolution performance of different ring band amplitude types, and find the 8-ring 0-1 amplitude type has the best super-resolution performance. Finally, the principle experimental device is built according to the simulation parameters, and the super-oscillatory device parameters is loaded onto the amplitude type spatial light modulator for the principle experiments, in which the super-oscillation foveated local super-resolution imaging system is able to perform high image contrast imaging in the whole field of view and super-resolution imaging in the foveated field of view area. As a result, this method achieves the 1.25 times super-resolution magnification in the foveated field of view area, which realizes the super-resolutio n imaging of local field while keeping the resolution of other fields unchanged. Experiments verify the feasibility and effectiveness of our system.

Novel insights about ribosomal DNA double strand break repair revealed by super-resolution imaging techniques and very fast CRISPR.

Ribosomal DNA (rDNA) is repetitive gene sequence that produces the RNA components for the translation machinery in eukaryotic cells - ribosomes. The maintenance of rDNA genome stability against double-strand breaks (DSBs) is critical regarding cellular aging related diseases and tumor development due to its repetitive nature and distribution over multiple chromosomes. Previous studies have shown that DSB within rDNA region will induce rDNA transcriptional repression and nucleolar segregation. However, it remains poorly understood regarding the kinetics of associated transcriptional regulation, the architecture of the nucleolar cap, and the link between them, likely due to the resolution limit of conventional imaging tools and the absence of proper system that can rapidly induce DSBs specific to rDNA region with accurately controlled timing. To resolve these limitations and provide deeper insights on how rDNA DSB repair response is regulated, we use self-built super-resolution fluorescence imaging systems, e.g., stimulated emission depletion microscopy, which allow to visualize nucleolar structures beyond the diffraction limit, and lattice light sheet microscopy, which enables to monitor fast kinetics of the repair process with minimal photo-induced disturbance, combined with a recently developed rapidly-inducible photo-caged CRISPR-Cas9 system (very fast CRISPR, vfCRISPR) in our lab, to study the spatiotemporal coordination of the DSB repair factor assembly upon rDNA DSB damage, and dissect its important role in regulating pathway choice and outcome fidelity.

Dual-channel structured illumination super-resolution quantitative fluorescence resonance energy transfer imaging

The Structured illumination (SI)-based super resolution fluorescence resonance energy transfer (SR-FRET) imaging technique, known as SISR-FRET, enables the investigation of molecular structures and functions in cellular organelles by resolving sub-diffraction FRET signals within living cells. The FRET microscopy offers unique advantages for quantitatively detecting dynamic interactions and spatial distribution of biomolecules within living cells. The spatial resolution of conventional FRET microscopy is limited by the diffraction limit, and it can only capture the average behavior of these events within the resolution limits of conventional fluorescence microscopy. The SISR-FRET performs sequential linear reconstruction of the three-channel SIM images followed by FRET quantitative analysis by using a common localization mask-based filtering approach. This two-step process ensures the fidelity of the reconstructed SR-FRET signals while effectively removing false-positive FRET signals caused by SIM artifacts. However, the slow imaging speed resulting from the switching of excitation-emission channels in SISR-FRET imaging limits its application in fast imaging scenarios. To address this issue, this study proposes a dual-channel structured illumination super-resolution quantitative FRET imaging system and method. By incorporating an FRET dual-channel imaging and registration module into the imaging pathway, the spatial switching and channel multiplexing of the SISR-FRET excitation-emission channels are achieved. Combining the image reconstruction algorithm with channel sub-pixel registration correction, the dual-channel SISR-FRET technique enhances the temporal resolution by 3.5 times while preserving the quantitative super-resolution FRET analysis. Experimental results are obtained by using a multi-color SIM system to perform super-resolution imaging of living cells expressing mitochondria outer membrane FRET standard plasmids. These experiments validate the improved spatial and temporal resolution of dual-channel SISR-FRET and the fidelity of FRET quantification analysis. In summary, this research presents a novel dual-channel structured illumination super-resolution FRET imaging system and method. It overcomes the limitations of slow imaging speed in SISR-FRET by realizing the spatial switching and channel multiplexing of excitation-emission channels. The proposed technique enhances the temporal resolution while maintaining quantitative analysis of super-resolution FRET. Experimental validation demonstrates the increased spatial and temporal resolution of dual-channel SISR-FRET and the accuracy of FRET quantification analysis. This advancement contributes to the study of molecular structures and functions in cellular organelles, providing valuable insights into the intricate mechanisms of living cells.

Spectral Clustering Super-Resolution Imaging Based on Multispectral Camera Array.

Although multispectral and hyperspectral imaging acquisitions are applied in numerous fields, the existing spectral imaging systems suffer from either low temporal or spatial resolution. In this study, a new multispectral imaging system-camera array based multispectral super resolution imaging system (CAMSRIS) is proposed that can simultaneously achieve multispectral imaging with high temporal and spatial resolutions. The proposed registration algorithm is used to align pairs of different peripheral and central view images. A novel, super-resolution, spectral-clustering-based image reconstruction algorithm was developed for the proposed CAMSRIS to improve the spatial resolution of the acquired images and preserve the exact spectral information without introducing false information. The reconstructed results showed that the spatial and spectral quality and operational efficiency of the proposed system are better than those of a multispectral filter array (MSFA) based on different multispectral datasets. The PSNR of the multispectral super-resolution images obtained by the proposed method were respectively higher by 2.03 and 1.93 dB than those of GAP-TV and DeSCI, and the execution time was significantly shortened by approximately 54.55 s and 9820.19 s when the CAMSI dataset was used. The feasibility of the proposed system was verified in practical applications based on different scenes captured by the self-built system.

Research on spatial frequency shift super-resolution imaging based on evanescent wave illumination

<sec>In spite of the success of fluorescence microscopes (such as stimulated emission depletion microscopy, stochastic optical reconstruction microscopy and photoactivated localization microscopy) in biomedical field, which have realized nanometer scale imaging resolution and promoted the great development of bio-medicine, the super-resolution imaging method for non-fluorescent sample is still scarce, and the resolution still has a big gap to nanometer scale. Among existing methods, structured illumination microscopy, PSF engineering, super-oscillatory lens and microsphere assisted nanoscopy are more mature and widely used. However, limited by the theory itself or engineering practice, the resolutions of these methods are hard to exceed 50 nm, which limits their applications in many fields. Enlightened by synthetic aperture technique, researchers have proposed spatial frequency shift super-resolution microscopy through shifting and combining the spatial frequency spectrum of imaging target, which is a promising super-resolution imaging scheme, for its resolution limit can be broken through continually. Currently, owing to the limitation of the refractive index of optical material, the wavelength of illumination evanescent wave is hard to shorten when this wave is generated at prism surface via total internal reflection, which determines the highest resolution of this spatial frequency shift super-resolution imaging system. Another deficiency of this scheme is the difference in imaging resolution among different directions, for the image has the highest resolution only in the direction along the wave vector of illumination evanescent wave; while, the image has the lowest resolution in the direction perpendicular to the wave vector, which is the same as that obtained by far-field illumination.</sec><sec>In order to solve the above thorny questions, a new model of generating the evanescent wave is proposed, which can generates an omnidirectional evanescent wave with arbitrary wavelength based on the phase modulation of nano-structure, and solve the both problem in imaging system at the same time. To verify the our scheme, we set up a complete simulation model for spatial frequency shift imaging scheme, which includes three parts: the generation of evanescent wave and the interaction of the evanescent wave with the nano-structures at imaging target, which can be simulated with FDTD algorithm; the propagation of light field from near-field to far-field region, from the sample surface to the focal plane of objective lens, which can be calculated with angular spectrum theory; the propagation of light field from the focal place to the image plane, which can be worked out with Chirp-Z transform.</sec><sec>Firstly, with this complete simulation model, we compare the resolution of microscopy illuminated by evanescent wave with that by propagating wave. The experimental results verify the super-resolution imaging ability of evanescent wave illumination and the influence of prism refractive index. The higher the refractive index, the shorter the wavelength of evanescent wave is and the higher the resolution of spatial frequency shift imaging system. Secondly, we demonstrate the resolution difference in a series of directions with a three-bar imaging target rotated to different directions. The result shows that the highest imaging resolution occurs in the direction of illumination evanescent wave vector, and the lowest resolution appears in the direction perpendicular to the wave vector. Finally, we simulate the evanescent wave generated by nano-strcuture and demonstrate its properties of wavelength and vector direction. When applied to near-field illumination super-resolution imaging, the omnidirectional evanescent wave solves the both problems in the model of total internal reflection from the prism surface.</sec><sec>Therefore, the advantages of our scheme are higher imaging resolution and faster imaging speed, no need for multi-direction and multiple imaging, and also image post-processing. In this study, a new spatial frequency shift super-resolution imaging method is proposed, which lays a theoretical foundation for its applications.</sec>

Minimizing the Optical Illusion of Nanoparticles in Single Cells Using Four-Dimensional Cuboid Multiangle Illumination-Based Light-Sheet Super-Resolution Imaging.

Although light-sheet-based super-resolution microscopy is an excellent detection technique for biological samples because of minimal photodamage, uneven light paths due to solid-angle illumination limits it, resulting in an optical illusion. Furthermore, the optical illusion limits the observations of individual molecules in diffraction. In this study, a four-dimensional cuboid multiangle illumination-based light-sheet super-resolution (4D CMLS) imaging system was developed to minimize optical illusions in cells. The lab-built 4D CMLS imaging system was integrated with total internal reflection fluorescence and a differential interference contrast microscope. A specially designed rotatable cuboid prism simply overcame the optical illusion by rotating a specimen on the prism to change the direction of light coming from an illumination lens. 4D CMLS reconstructed images of nanoparticles of different sizes were acquired in multi-illumination angles of 0°, 90°, 180°, and 270°. Additionally, a 4D multiangle illumination-based algorithm was created to select the optimal illumination angle by combining three-dimensional super-resolution imaging with multiangle observation, even in the presence of obstacles. The 4D CMLS imaging method demonstrates the in-depth 4D observation of samples at an optimum angle that can be used in various applications, such as single-molecule and subcellular organelle observations in single cells at subdiffraction limit resolutions that describe the scenario of nature.

Simplified superoscillatory lenses for super-resolution imaging.

In recent years, superoscillations have become a new method for creating super-resolution imaging systems. The design of superoscillatory wavefronts and their corresponding lenses can, however, be a complicated process. In this study, we extend a recently developed method for designing complex superoscillatory filters to the creation of phase- and amplitude-only filters and compare their performance. These three types of filters can generate nearly identical superoscillatory fields at the image plane.

3-D Super-Resolution of Coded Aperture Millimeter-Wave Images Using Complex-Valued Convolutional Neural Network

Electromagnetic (EM) waves at millimeter-wave (mmW) frequencies have found applications in a variety of imaging systems, from security screening to defense and automotive radars, with the research and development of mmW imaging systems gaining interest in recent years. Despite their significant advantages, mmW imaging systems suffer from poor resolution compared to higher frequency reconstructions, such as optical images. To improve the resolution of mmW images, various super-resolution (SR) techniques have been introduced. One such technique is the use of machine learning algorithms in the signal processing layer of the imaging system without altering any of the system’s parameters. This article focuses on the use of a convolutional neural network (CNN) architecture to achieve SR when applied to 3-D mmW input images. To exploit the phase information content of the input images along with the magnitude, a complex-valued CNN is designed, which can accommodate complex-valued data. To simplify the learning process, the resolution difference between the input and output images is divided into smaller parts by using subnetworks in the CNN architecture. The trained model is tested on simulated and experimental targets. The average mean square error score and the structural similarity index obtained on a test dataset of 460 samples are 0.0127 and 0.9225, respectively. It can be inferred that the model has the capability to improve the resolution of input mmW images to a high degree of fidelity, hence paving the way for an end-to-end SR imaging system.

The miEye: Bench-top super-resolution microscope with cost-effective equipment

Commercial super-resolution (SR) imaging systems require a high budget, while current more affordable open source microscopy systems lack modularity and sometimes are too complex or lack reliability. We present miEye – a cost-effective microscope designed for high-resolution wide-field fluorescence imaging. The build is constructed using a CNC milled aluminum microscope body and commercially available optomechanics, with open-source Python-based microscope control, data visualization, and analysis software integration. The data acquisition software works robustly with commonly used industrial-grade complementary metal oxide semiconductor (iCMOS) cameras, performs IR beam back-reflection-based automatic focus stabilization, and allows for laser control via an Arduino-based laser relay. The open-source nature of the design is aimed to facilitate adaptation by the community. The build can be constructed for a cost of roughly 50 k €. It contains SM-fiber and MM-fiber excitation paths that are easy to interchange and an adaptable emission path. Also, it ensures <5 nm/min stability of the sample on all axes, and allows achieving <30 nm lateral resolution for dSTORM and DNA-PAINT single-molecule localization microscopy (SMLM) experiments. Thus it serves as a cost-effective and adaptable addition to the open source microscopy community and potentially will allow high-quality SR imaging even for limited-budget research groups.

An LED-Based structured illumination microscope using a digital micromirror device and GPU accelerated image reconstruction.

When combined with computational approaches, fluorescence imaging becomes one of the most powerful tools in biomedical research. It is possible to achieve resolution figures beyond the diffraction limit, and improve the performance and flexibility of high-resolution imaging systems with techniques such as structured illumination microscopy (SIM) reconstruction. In this study, the hardware and software implementation of an LED-based super-resolution imaging system using SIM employing GPU accelerated parallel image reconstruction is presented. The sample is illuminated with two-dimensional sinusoidal patterns with various orientations and lateral phase shifts generated using a digital micromirror device (DMD). SIM reconstruction is carried out in frequency space using parallel CUDA kernel functions. Furthermore, a general purpose toolbox for the parallel image reconstruction algorithm and an infrastructure that allows all users to perform parallel operations on images without developing any CUDA kernel code is presented. The developed image reconstruction algorithm was run separately on a CPU and a GPU. Two different SIM reconstruction algorithms have been developed for the CPU as mono-thread CPU algorithm and multi-thread OpenMP CPU algorithm. SIM reconstruction of 1024 × 1024 px images was achieved in 1.49 s using GPU computation, indicating an enhancement by ∼28 and ∼20 in computation time when compared with mono-thread CPU computation and multi-thread OpenMP CPU computation, respectively.

Implementation of a fluorescence spatiotemporal modulation super-resolution microscope.

Super-resolution microscopy (SRM) unveils details of subcellular organelles and provides a technical foundation for cellular biology research. Long-term, non-invasive live-cell super-resolution imaging requires low-intensity illumination and high image quality. Here, we present a new, to the best of our knowledge, method based on time-resolved detection termed fluorescence spatiotemporal modulation, in which highly spatially resolved photons in the beam center are extracted by taking the difference of the photons in the beam periphery with a weighted coefficient. The experimental results show a sub-100 nm resolution at tens of microwatts of laser power. Our proposed method requires only one laser, laying a foundation for a lower-cost multi-color super-resolution imaging system.

Super-resolution imaging based on radially polarized beam induced superoscillation using an all-dielectric metasurface.

Superoscillation is a kind of phenomenon which can generate oscillation faster than the fastest component of a band-limited function. For optics, superoscillation is generated by coherence of low spatial frequency waves. It can bring a localized region named "hot spot", which has a smaller size than the diffraction-limit, and this character has potential applicaions in super-resolution imaging. Using a high-order radially polarized Laguerre-Gaussian beam tightly focused by high-NA objective lens, we can easily obtain and control the superoscillation hot spot. Using a metasurface, which has compact volume and sub-wavelength pixel size, we can generate the high-order radially polarized Laguerre-Gaussian beam more simply than conventional methods like using a liquid crystal mode converter. We first analyze the properties of unit cells of the metasurface and simulate the performance of the metasurface. Then we analyze the property of the tightly focused high-order radially polarized Laguerre-Gaussian beam and design a super-resolution imaging system using our designed metasurface. Therefore, the 2-fold lateral resolution enhancement is realized in our approach. This method can be used to improve lateral resolution in conventional confocal imaging systems.

Flat-field multiplexed multifocal structured illumination super-resolution microscopy

Multifocal structured illumination microscopy (MSIM) can achieve optically sectioned images with twice the diffraction limited resolution at an imaging speed of 1 Hz and an imaging depth of up to 50 μm. Compared with the traditional wide-field SIM, the MSIM has greater imaging depth and optical sectionning ability, and it is more suitable for long-term three-dimensional (3D) super-resolution imaging of living thick samples. However, the MSIM has some problems, such as slow imaging speed and complex image post-processing process. In this work, a fast super-resolution imaging method and system based on the flat-field multiplexed MSIM (FM-MSIM) is proposed. By inserting a beam shaping device into the illumination light path, the Gaussian beam is reshaped into a uniform flat-top profile, thereby improving the intensity uniformity of excitation multi-spot focal array and expanding the field of view. By elongating each diffraction limited excitation focal point four times along the &lt;i&gt;Y&lt;/i&gt; direction to form a new multiplexed multifocal array pattern, the number of scanning steps is reduced, the energy utilization is improved, and then the imaging speed and signal-to-noise ratio are improved. Combined with the sparse Bayesian learning image reconstruction algorithm based on multiple measurement vector model, the image reconstruction steps are simplified, the imaging speed can be improved at least 4 times while ensuring the spatial resolution of MSIM. On this basis, the established FM-MSIM system is used to carry out the super-resolution imaging experiments on the BSC cell microtubule samples and mouse kidney slices. The experimental results prove the fast three-dimensional super-resolution imaging ability of the system, which is of great significance in developing the fast MSIM.

Aberration correction of aperture-divided off-axis simultaneous polarization super-resolution imaging optical system

According to the requirements for broadband simultaneous polarization high-resolution imaging, a divided-aperture simultaneous polarization super-resolution imaging system based on reflective free-form surface optical system and digital micro-mirror device is proposed. It has the advantages of wide working wavelength band, simultaneous imaging of multiple polarization states, single detector, high resolution and lightweight. The aberration correction principle and design optimization method of the optical structure for this imaging system are given. The Wassermann-Wolf theory is further developed, and the reflective Wassermann-Wolf differential equations that eliminate a variety of aberrations are derived. At the same time, combined with Seidel aberration theory and using iterative method, the distortion elimination boundary condition is added when solving the Wassermann-Wolf equation. Through the iterative method, the optical initial structure is obtained, which can correct spherical aberration, coma, astigmatism and distortion at the same time. The initial structure is subjected to off-axis treatment and further optimized, and the user-defined optimization evaluation function is written to strictly control the position of the light falling point of each sub aperture and each field of view on the middle image plane and the final image plane, so as to effectively suppress the distortion in the final system and avoid the mismatch error between the mirror element and the pixel in the process of super-resolution reconstruction. The reconstruction quality can be improved. Finally, the design of the four-sub-aperture free-form surface off-axis reflective super-resolution imaging optical system is completed, which possesses a large relative aperture (&lt;i&gt;F&lt;/i&gt;# = 2.5) and compact structure. The imaging quality of each polarization channel is close to the diffraction limit. The above aberration correction principle and the image quality optimization method can effectively guide the design of the wide band simultaneous polarization super-resolution imaging optical system.