It is well known that passive image correction of turbulence distortions often involves using geometry-dependent deconvolution algorithms. On the other hand, active imaging techniques using adaptive optic correction should use the distorted wavefront information for guidance. Our work shows that a hybrid hardware-software approach is possible to obtain accurate and highly detailed images through turbulent media. The processing algorithm also takes much fewer iteration steps in comparison with conventional image processing algorithms. In our proposed approach, a plenoptic sensor is used as a wavefront sensor to guide post-stage image correction on a high-definition zoomable camera. Conversely, we show that given the ground truth of the highly detailed image and the plenoptic imaging result, we can generate an accurate prediction of the blurred image on a traditional zoomable camera. Similarly, the ground truth combined with the blurred image from the zoomable camera would provide the wavefront conditions. In application, our hybrid approach can be used as an effective way to conduct object recognition in a turbulent environment where the target has been significantly distorted or is even unrecognizable.
Large temperature gradients are a known source of strong atmospheric turbulence conditions. Often times these areas of strong turbulence conditions are also accompanied by conditions that make it difficult to conduct long term optical atmospheric tests. The Shuttle Landing Facility (SLF) at the Kennedy Space Center (KSC) provides a prime testing environment that is capable of generating strong atmospheric turbulence yet is also easily accessible for well instrumented testing. The Shuttle Landing Facility features a 5000 m long and 91 m wide concrete runway that provides ample space for measurements of atmospheric turbulence as well as the opportunity for large temperature gradients to form as the sun heats the surface. We present the results of a large aperture LED scintillometer, a triple aperture laser scintillometer, and a thermal probe system that were used to calculate a path averaged and a point calculation of Cn2. In addition, we present the results of the Plenoptic Sensor that was used to calculate a path averaged Cn2 value. These measurements were conducted over a multi-day continuous test with supporting atmospheric and weather data provided by the University of Central Florida.
The image encryption and decryption technique using lens components and random phase screens has attracted a great deal of research interest in the past few years. In general, the optical encryption technique can translate a positive image into an image with nearly a white speckle pattern that is impossible to decrypt. However, with the right keys as conjugated random phase screens, the white noise speckle pattern can be decoded into the original image. We find that the fundamental ideas in image encryption can be borrowed and applied to carry out beam corrections through turbulent channels. Based on our detailed analysis, we show that by using two deformable mirrors arranged in similar fashions as in the image encryption technique, a large number of controllable phase and amplitude distribution patterns can be generated from a collimated Gaussian beam. Such a result can be further coupled with wavefront sensing techniques to achieve laser beam correction against turbulence distortions. In application, our approach leads to a new type of phase conjugation mirror that could be beneficial for directed energy systems.
A plenoptic sensor can be used to improve the image formation process in a conventional camera. Through this process, the conventional image is mapped to an image array that represents the image’s photon paths along different angular directions. Therefore, it can be used to resolve imaging problems where severe distortion happens. Especially for objects observed at moderate range (10m to 200m) through turbulent water, the image can be twisted to be entirely unrecognizable and correction algorithms need to be applied. In this paper, we show how to use a plenoptic sensor to recover an unknown object in line of sight through significant water turbulence distortion. In general, our approach can be applied to both atmospheric turbulence and water turbulence conditions.
Adaptive optics relies on the accuracy and speed of a wavefront sensor in order to provide quick corrections to distortions in the optical system. In weaker cases of atmospheric turbulence often encountered in astronomical fields, a traditional Shack-Hartmann sensor has proved to be very effective. However, in cases of stronger atmospheric turbulence often encountered near the surface of the Earth, atmospheric turbulence no longer solely causes small tilts in the wavefront. Instead, lasers passing through strong or “deep” atmospheric turbulence encounter beam breakup, which results in interference effects and discontinuities in the incoming wavefront. In these situations, a Shack-Hartmann sensor can no longer effectively determine the shape of the incoming wavefront. We propose a wavefront reconstruction and correction algorithm based around the plenoptic sensor. The plenoptic sensor’s design allows it to match and exceed the wavefront sensing capabilities of a Shack-Hartmann sensor for our application. Novel wavefront reconstruction algorithms can take advantage of the plenoptic sensor to provide a rapid wavefront reconstruction necessary for real time turbulence. To test the integrity of the plenoptic sensor and its reconstruction algorithms, we use artificially generated turbulence in a lab scale environment to simulate the structure and speed of outdoor atmospheric turbulence. By analyzing the performance of our system with and without the closed-loop plenoptic sensor adaptive optics system, we can show that the plenoptic sensor is effective in mitigating real time lab generated atmospheric turbulence.
There are many techniques to achieve basic wavefront sensing tasks in the weak atmospheric turbulence regime. However, in strong and deep turbulence situations, the complexity of a propagating wavefront increases significantly. Typically, beam breakup will happen and various portions of the beam will randomly interfere with each other. Consequently, some conventional techniques for wavefront sensing turn out to be inaccurate and misleading. For example, a Shack-Hartmann sensor will be confused by multi-spot/zero-spot result in some cells. The curvature sensor will be affected by random interference patterns for both the image acquired before the focal plane and the image acquired after the focal plane. We propose the use of a plenoptic sensor to solve complex wavefront sensing problems. In fact, our results show that even for multiple beams (their wavelengths can be the same) passing through the same turbulent channel, the plenoptic sensor can reconstruct the turbulence-induced distortion accurately. In this paper, we will demonstrate the plenoptic mapping principle to analyze and reconstruct the complex wavefront of a distorted laser beam.
Adaptive optics has been widely used in the field of astronomy to correct for atmospheric turbulence while viewing images of celestial bodies. The slightly distorted incoming wavefronts are typically sensed with a Shack-Hartmann sensor and then corrected with a deformable mirror. Although this approach has proven to be effective for astronomical purposes, a new approach must be developed when correcting for the deep turbulence experienced in ground to ground based optical systems. We propose the use of a modified plenoptic camera as a wavefront sensor capable of accurately representing an incoming wavefront that has been significantly distorted by strong turbulence conditions (C2n <10-13 m- 2/3). An intelligent correction algorithm can then be developed to reconstruct the perturbed wavefront and use this information to drive a deformable mirror capable of correcting the major distortions. After the large distortions have been corrected, a secondary mode utilizing more traditional adaptive optics algorithms can take over to fine tune the wavefront correction. This two-stage algorithm can find use in free space optical communication systems, in directed energy applications, as well as for image correction purposes.
When a beam propagates through atmospheric turbulence over a known distance, the target beam profile deviates from the projected profile of the beam on the receiver. Intuitively, the unwanted distortion provides information about the atmospheric turbulence. This information is crucial for guiding adaptive optic systems and improving beam propagation results. In this paper, we propose an entropy study based on the image from a plenoptic sensor to provide a measure of information content of atmospheric turbulence. In general, lower levels of atmospheric turbulence will have a smaller information size while higher levels of atmospheric turbulence will cause significant expansion of the information size, which may exceed the maximum capacity of a sensing system and jeopardize the reliability of an AO system. Therefore, the entropy function can be used to analyze the turbulence distortion and evaluate performance of AO systems. In fact, it serves as a metric that can tell the improvement of beam correction in each iteration step. In addition, it points out the limitation of an AO system at optimized correction as well as the minimum information needed for wavefront sensing to achieve certain levels of correction. In this paper, we will demonstrate the definition of the entropy function and how it is related to evaluating information (randomness) carried by atmospheric turbulence.
Atmospheric turbulence can significantly affect imaging through paths near the ground. Atmospheric turbulence is generally treated as a time varying inhomogeneity of the refractive index of the air, which disrupts the propagation of optical signals from the object to the viewer. Under circumstances of deep or strong turbulence, the object is hard to recognize through direct imaging. Conventional imaging methods can’t handle those problems efficiently. The required time for lucky imaging can be increased significantly and the image processing approaches require much more complex and iterative de-blurring algorithms. We propose an alternative approach using a plenoptic sensor to resample and analyze the image distortions. The plenoptic sensor uses a shared objective lens and a microlens array to form a mini Keplerian telescope array. Therefore, the image obtained by a conventional method will be separated into an array of images that contain multiple copies of the object’s image and less correlated turbulence disturbances. Then a highdimensional lucky imaging algorithm can be performed based on the collected video on the plenoptic sensor. The corresponding algorithm will select the most stable pixels from various image cells and reconstruct the object’s image as if there is only weak turbulence effect. Then, by comparing the reconstructed image with the recorded images in each MLA cell, the difference can be regarded as the turbulence effects. As a result, the retrieval of the object’s image and extraction of turbulence effect can be performed simultaneously.
Atmospheric turbulence adds accumulated distortion to images obtained by cameras and surveillance systems. When the turbulence grows stronger or when the object is further away from the observer, increasing the recording device resolution helps little to improve the quality of the image. Many sophisticated methods to correct the distorted images have been invented, such as using a known feature on or near the target object to perform a deconvolution process, or use of adaptive optics. However, most of the methods depend heavily on the object’s location, and optical ray propagation through the turbulence is not directly considered. Alternatively, selecting a lucky image over many frames provides a feasible solution, but at the cost of time. In our work, we propose an innovative approach to improving image quality through turbulence by making use of a modified plenoptic camera. This type of camera adds a micro-lens array to a traditional high-resolution camera to form a semi-camera array that records duplicate copies of the object as well as “superimposed” turbulence at slightly different angles. By performing several steps of image reconstruction, turbulence effects will be suppressed to reveal more details of the object independently (without finding references near the object). Meanwhile, the redundant information obtained by the plenoptic camera raises the possibility of performing lucky image algorithmic analysis with fewer frames, which is more efficient. In our work, the details of our modified plenoptic cameras and image processing algorithms will be introduced. The proposed method can be applied to coherently illuminated object as well as incoherently illuminated objects. Our result shows that the turbulence effect can be effectively suppressed by the plenoptic camera in the hardware layer and a reconstructed “lucky image” can help the viewer identify the object even when a “lucky image” by ordinary cameras is not achievable.
Enhanced backscatter effects have long been predicted theoretically and experimentally demonstrated. The reciprocity of a turbulent channel generates a group of paired rays with identical trajectory and phase information that leads to a region in phase space with double intensity and scintillation index. Though simulation work based on phase screen models has demonstrated the existence of the phenomenon, few experimental results have been published describing its characteristics, and possible applications of the enhanced backscatter phenomenon are still unclear. With the development of commercially available high powered lasers and advanced cameras with high frame rates, we have successfully captured the enhanced backscatter effects from different reflection surfaces. In addition to static observations, we have also tilted and pre-distorted the transmitted beam at various frequencies to track the dynamic properties of the enhanced backscatter phenomenon to verify its possible application in guidance and beam and image correction through atmospheric turbulence. In this paper, experimental results will be described, and discussions on the principle and applications of the phenomenon will be included. Enhanced backscatter effects are best observed in certain levels of turbulence (Cn2≈10-13 m-2/3), and show significant potential for providing self-guidance in beam correction that doesn’t introduce additional costs (unlike providing a beacon laser). Possible applications of this phenomenon include tracking fast moving object with lasers, long distance (>1km) alignment, and focusing a high-power corrected laser beam over long distances.
Adaptive optics methods have long been used by researchers in the astronomy field to retrieve correct images of celestial bodies. The approach is to use a deformable mirror combined with Shack-Hartmann sensors to correct the slightly distorted image when it propagates through the earth’s atmospheric boundary layer, which can be viewed as adding relatively weak distortion in the last stage of propagation. However, the same strategy can’t be easily applied to correct images propagating along a horizontal deep turbulence path. In fact, when turbulence levels becomes very strong (Cn2>10-13 m-2/3), limited improvements have been made in correcting the heavily distorted images. We propose a method that reconstructs the light field that reaches the camera, which then provides information for controlling a deformable mirror. An intelligent algorithm is applied that provides significant improvement in correcting images. In our work, the light field reconstruction has been achieved with a newly designed modified plenoptic camera. As a result, by actively intervening with the coherent illumination beam, or by giving it various specific pre-distortions, a better (less turbulence affected) image can be obtained. This strategy can also be expanded to much more general applications such as correcting laser propagation through random media and can also help to improve designs in free space optical communication systems.
A plenoptic camera is a camera that can retrieve the direction and intensity distribution of light rays collected by the camera and allows for multiple reconstruction functions such as: refocusing at a different depth, and for 3D microscopy. Its principle is to add a micro-lens array to a traditional high-resolution camera to form a semi-camera array that preserves redundant intensity distributions of the light field and facilitates back-tracing of rays through geometric knowledge of its optical components. Though designed to process incoherent images, we found that the plenoptic camera shows high potential in solving coherent illumination cases such as sensing both the amplitude and phase information of a distorted laser beam. Based on our earlier introduction of a prototype modified plenoptic camera, we have developed the complete algorithm to reconstruct the wavefront of the incident light field. In this paper the algorithm and experimental results will be demonstrated, and an improved version of this modified plenoptic camera will be discussed. As a result, our modified plenoptic camera can serve as an advanced wavefront sensor compared with traditional Shack- Hartmann sensors in handling complicated cases such as coherent illumination in strong turbulence where interference and discontinuity of wavefronts is common. Especially in wave propagation through atmospheric turbulence, this camera should provide a much more precise description of the light field, which would guide systems in adaptive optics to make intelligent analysis and corrections.