Sparse-aperture photonics-integrated interferometer (SPIN) imaging system: structural design and imaging quality analysis.

For traditional imaging systems, high imaging quality and system miniaturization are often contradictory. In order to meet the requirements of high imaging quality and system miniaturization, this paper proposes a method to correct the aberration of coherent imaging optical systems. The method is based on the idea of phase recovery and the imaging principle of a coherent imaging system to recover the aberrations at the exit pupil of the system. According to the recovered aberrations, conjugate filters are constructed to correct the image quality in the frequency domain. The imaging quality of the system is improved without changing the original optical path, and the simplicity of the system is guaranteed. To solve the pupil frequency domain aberration more accurately, this paper adopts the dual competition and parallel recombination strategy based on the genetic algorithm and introduces the disaster model. The improved genetic algorithm can effectively restrain the appearance of the “precocity” phenomenon. Finally, the paraxial imaging optical path is simulated and verified by experiments. The results show that, after aberration correction, the image sharpness is improved and the edge information is richer, which verifies the feasibility of the coherent imaging system image quality enhancement method proposed in this paper.

The optical transfer function (OTF), which correspond to the frequency domain, is of fundamental importance in characterizing imaging ability in optical imaging systems. By using the Collins formula and the optical transfer matrix theory, a simple and unified analytical expression of OTF is presented in any ghost imaging (GI) system. By comparing the spectrum distribution of OTF between different GI systems, one can predict which imaging system can provide better imaging quality when the same imaging object is used. Theoretical and experimental results are also implemented to verify our results.

A novel anti-cat-eye effect imaging technique based on wavefront coding is proposed as a solution to the problem of previous anti-cat-eye effect imaging techniques where imaging quality was sacrificed to reduce the retroreflection from the photoelectric imaging equipment. With the application of the Fresnel–Kirchhoff diffraction theory, and the definition of generalized pupil function combining both phase modulation and defocus factors, the cat-eye echo formation of the wavefront coded imaging system is theoretically modeled. Based on the physical model, the diffracted spot profile distribution and the light intensity distribution on the observation plane are further simulated with the changes in the defocus parameter and the phase modulation coefficient. A verification test on the cat-eye laser echo power of the wavefront coded imaging system and that of the conventional imaging system at a 20 m distance are conducted, respectively. Simulations and experiment results show that compared with conventional imaging systems, the wavefront coding imaging system can reduce the retroreflection echo by two orders of magnitude while maintaining better imaging quality through defocusing.

Optical imaging systems are widely used in various video surveillance sites, which may endure various harsh environmental aging conditions such as salt mist, change of temperature. However, there are few studies on the impact of various environmental tests on the overall imaging performance of the system. In this paper, several common environmental tests are selected to analyze their quantitative impact on the imaging quality of typical imaging systems. The imaging resolution, color revent and gray scale value are selected as the main imaging parameters. The study found that the salt mist test, gas corrosion, damp heat test, high and low temperature shock, and ultraviolet test have a great impact on the optical imaging system. Long-term exposure will cause the imaging quality of the imaging system to decrease significantly, with typical parameters attenuated by more than 10%. High temperature test, low temperature test, vibration test, waterproof test, low air pressure, shock and dust test have little effect on its image quality, the system has good tolerance to it, and the typical parameter attenuation is below 5%. This paper will provide some reference for the rational use of optical imaging systems and the compilation of test standards.

We demonstrate a method of optical tomography for surface and sub-surface imaging of biological tissues, based on the principle of wide field optical coherence tomography and capable of providing full-color three-dimensional views of a tissue structure. Contour or tomographic images are obtained with an interferometric imaging system using broadband light sources. The interferometric images are analyzed in the three color channels and recombined to generate 3D microscopic images of tissue structures with full natural color representation. In contrast to most existing three-dimensional microscopy methods, the presented technique allows monitoring of tissue structures close to its natural color, and can provide critical information for the physiological and pathological applications.

Abstract. As remote sensing and variable-rate technology are becoming more available for aerial applicators, practical methodologies for effective integration of these technologies are needed for site-specific aerial applications of crop production and protection materials. The objectives of this study were to demonstrate how to integrate an airborne multispectral imaging system and an IntelliStar variable-rate aerial application system for site-specific management of the winter weed henbit. The airborne imaging system was used to acquire natural color and near-infrared (NIR) images of a fallow field near College Station, Texas, for mapping the infestation of henbit shortly before herbicide application. The images were then rectified, classified, and converted to a binary prescription map with the full application rate on infested areas and the zero rate on non-infested areas. The variable-rate aerial application system mounted on an agricultural aircraft was used to apply glyphosate over the field based on the prescription map. Airborne imagery was collected 14 days after the herbicide application. The as-applied map along with the prescription map and the post-application imagery were used to assess the performance of the site-specific application. Spatial and statistical analysis results showed that the imaging system was effective for mapping henbit infestations and for assessing the performance of site-specific herbicide application, and that the variable-rate system accurately delivered the product at the desired rate to the prescribed areas for effective control of the weed. The methodology and results from this study will be useful for aerial applicators to incorporate airborne imaging and variable-rate application systems into their aerial application business to increase their capabilities and profits. Keywords: Aerial application, As-applied map, Henbit, Imaging system, Prescription map, Variable-rate technology.

Active Terahertz-wave imaging systems play a significant role in security and surveillance applications. This paper describes a 0.14THz near-field imaging system, which consists of a signal generator and acquisition unit, a transceiver front end, a digital signal process unit and a motor control unit. Base on the two-dimensional synthetic aperture technique and the image reconstruction algorithm, this system is capable of producing three-dimensional images of 2mm lateral resolution and 3cm range resolution in concealed weapon detection experiments.

3D imaging of solid targets using plenoptic cameras has been extensively explored and optimized over the years. Unfortunately, these imaging techniques, typically making use of triangulation methods and contrast recognition for depth estimation, lose their validity when imaging translucent media. For these cases, tomographic reconstruction has been shown to be a promising avenue for recovering the 3D shape of a translucent volume. Apart from the tomographic reconstruction algorithm itself, the accuracy of a reconstructed solution depends on the set of measured projections and on the system matrix. A proper determination of the system matrix is key as its elements describe the weighted contribution of a voxel in object space to one in image space; however, computing the matrix elements can consist of an arduous task as it requires a priori knowledge of the imaging system and precise modeling of the physical properties of the acquisition process. In this work, we present how an optical design software can be used to generate such system matrices. Compared with approximation methods involving paraxial ray tracing, the proposed method offers the main advantage of real ray tracing, in which the computed weighted contributions intrinsically account for optical aberrations in the imaging system. Physical properties of light propagation within the translucent medium can also be taken into account when using non-sequential modes. Using a ray tracing software thus offers great flexibility in designing plenoptic imaging systems used with 3D tomographic reconstruction techniques.

Optical imaging usually suffers from aberrations that are induced by various structures when imaging biological samples. Usually aberrations degrade the imaging system performances by broadening the point spread function (PSF). Unexpectedly we show that in spatially incoherent interferometry like full-filed optical coherence tomography (FFOCT), the system PSF width is almost insensitive to aberrations. Instead of considering the PSF of a classical imaging system such as a microscope, we specifically pay attention to the system PSF of interferometric imaging systems for which an undistorted wavefront from a reference beam interferes with the distorted wavefront of the object beam. By comparing the cases of scanning OCT with spatially coherent illumination, wide-field OCT with spatially coherent illumination and FFOCT with spatially incoherent illumination, we found that in FFOCT with spatially incoherent illumination the system PSF width is almost independent of the aberrations and only its amplitude varies. This is demonstrated by theoretical analysis as well as numerical calculations for different aberrations, and confirmed by experiments with a FFOCT system. It is the first time to the best of our knowledge that such specific merit of incoherent illumination in FFOCT has been demonstrated. Based on this, the signal level is used as metric in our adaptive optics FFOCT system for retinal imaging. Only the main aberrations (defocus and astigmatism) that are dominating in eye are corrected to improve the signal to noise ratio and the high order aberrations are skipped. This would increase the correction speed thus reducing the imaging time.

Metasurface has drawn extensive attention due to its capability of modulating light with a high degree of freedom through ultrathin and sub-wavelength optical elements, and metalens, as one of its important applications, promises to replace the bulky refractive optics, facilitating the imaging system light-weight and compact characteristics. Besides, computer-generated holography (CGH) is of substantial interest for three-dimensional (3D) imaging technology by virtue of its ability of restoring the whole optical wave field and re-constructing the true 3D scene. Consequently, the combination of metalens and CGH holds transformative potential in enabling the miniaturization of 3D imaging systems. However, its imaging performance is subject to the aberrations and speckle noises originating from the metalens and CGH. Inspired by recent progress that computational imaging can be applied to close the gap, a novel full-color imaging system, adopting end-to-end joint optimization of metalens and CGH for high imaging quality, is proposed in this paper. The U-net based network as the pre-processing adjusts weights to make the holographic reconstruction offset imaging defects, incorporating the imaging processing into the step of generating hologram. Optimized by deep learning, the proposed imaging system is capable of full-color imaging with high fidelity in a compact form factor, envisioned to take an essential step towards the high-performance miniaturized imaging system.

Medical images are acquired for the purpose of gathering information regarding the disease state of a patient. The quality of the image should be a measure of how a specified task may be performed given the resulting image. Image quality is task dependent; one imaging system may provide images that allow better task performance than another system's for one task, but worse for another task. Determining the quality of an imaging system involves specifying the task of interest, the range of objects that will be imaged, and the observer (human or machine reader) who will perform the task. In radiography it has become common to use Fourier measures to describe image quality through a combination of Fourier‐based measures of system resolution and noise. The Line Spread Function, when Fourier transformed, yields the Modulation Transfer Function (MTF) as a measure of system resolution. Use of the MTF to describe a system's resolution is appropriate when the imaging system is shift‐invariant, that is, the line spread function is independent of position. Image noise is described in the Fourier domain by the Noise Power Spectrum (NPS). We can use the NPS to describe the noise in an imaging system whenever the noise properties are stationary, meaning that the variance and correlations between fluctuations in different locations are not dependent on their absolute location. These Fourier measures of system resolution and noise are commonly combined to give an overall figure of merit known as the Detective Quantum Efficiency (DQE). The DQE describes the signal‐to‐noise transfer characteristics of an imaging system as long as those assumptions of shift‐invariance and noise stationarity are valid. In digital systems the image of an object is affected by the location of the object with respect to the pixel grid. In other words, the detector pixels cause the system to be shift‐variant. In this case the MTF does not describe the resolution properties completely. This is particularly the case for tomographic systems, where the point‐response function is quite position‐dependent. Moreover, in real imaging systems the noise properties will depend on position, most notably because real patients always have structure. So, the Fourier‐domain noise concept of Noise Power Spectrum does not capture all the properties of noise for real imaging systems and tasks. In this talk we will consider a general treatment of the imaging system as a mapping of information from the patient to the data, without the assumptions inherent in Fourier analysis. We will discuss approaches to the characterization of system resolution and noise in terms of position‐dependent parameters. Once such position‐dependent imaging properties of a system are determined, we can use them to calculate measures of image quality that summarize the usefulness of the images for the performance of various visual tasks.

A simple multispectral classification method for the identification of systemically diseased chickens was developed and tested between two different imaging systems. An image processing algorithm was developed to define and locate the region of interest (ROI) as classification areas on the image. The average intensity was calculated for each classification area of the chicken image. A decision tree algorithm was used to determine threshold values for each classification areas. The wavelength of 540 nm was used for image differentiation purpose. There were 164 wholesome and 176 systemically diseased chicken images collected using the first imaging system, and 332 wholesome and 318 systemically diseased chicken images taken by the second imaging system. The differentiation thresholds, generated by the decision tree method, based on the images from the first imaging system were applied to the images from the second imaging system, and vice versa. The accuracy from evaluation was 95.7% for wholesome and 97.7% of systemically diseased chickens for the first image batch, and 99.7% for wholesome and 93.5% for systemically diseased chickens for the second image batch. The result showed that using single wavelength and threshold, this simple classification method can be used in automated on-line applications for chicken inspection.

Imaging systems using aspheric imaging lenses with complementary computation can deliver performance unobtainable in conventional imaging systems. These new imaging systems, termed Wavefront coded imaging systems, use specialized optics to capture a coded image of the scene. Decoding the intermediate image provides the "human-usable" image expected of an imaging system. Computation for the decoding step can be made completely transparent to the user with today's technology. Real-time Wavefront coded systems are feasible and cost-effective. This "computational imaging" technology can be adapted to solve a wide range of imaging problems. Solutions include the ability to provide focus-free imaging, to increase the field of view, to increase the depth of read, to correct for aberrations (even in single lens systems), and to account for assembly and temperature induced misalignment. Wavefront coded imaging has been demonstrated across a wide range of applications, including microscopy, miniature cameras, machine vision systems, infrared imaging systems and telescopes.

Conventional multispectral imaging systems based on bandpass filters struggle to record multispectral videos with high spatial resolutions because of their limited light efficiencies. This paper proposes a multi-aperture multispectral imaging system based on notch filters that overcomes this limitation by allowing light from most of the spectrum to pass through. Based on this imaging principle, a prototype multi-aperture multispectral imaging system comprising notch filters was built and demonstrated. Further, a dictionary learning- and total variation-based spectral super-resolution algorithm was developed to reconstruct spectral images. The simulation results obtained using public multispectral datasets showed that, compared to the dictionary learning-based spectral super-resolution algorithm, the proposed algorithm reconstructed the spectral information with a higher accuracy and removed noise, and the verification experiments confirmed the performance efficiency of the prototype system. The experimental results showed that the proposed imaging system can capture images with high spatial and spectral resolutions under low illumination conditions. The proposed algorithm improved the spectral resolution of the acquired data from 9 to 31 bands, and the average peak signal-to-noise ratio remained above 43 dB, which is 13 dB higher than those of the state-of-the-art coded aperture snapshot spectral imaging methods. Simultaneously, the frame rate of the imaging system was up to 5000 frames/s under natural daylight.

A liquid lens is used to realize an adaptive interferometric particle imaging system. The defocus parameter of the system can be changed instantaneously by adjusting the voltage applied to the lens. This enables adjusting the imaging conditions in real time. The setup is first tested on programmable rough particles generated by a digital micromirror device (DMD), and then with real glass particles under nanosecond pulse illumination.