Kenneth S. Kubala

Reducing complexity in computational imaging systems

Traditional methods of optical design trade optical system complexity for image quality. High quality imagers often require high system complexity. A new imaging methodology called Wavefront Coding uses aspheric optics and signal processing in order to reduce system complexity and deliver high quality imagery. An example in terms of a conformal IR imaging system is given.

Design and optimization of aberration and error invariant space telescope systems

Telescope performance is often limited by aberrations, and/or fabrication and alignment errors. Additionally, image formation in large space-based systems is sensitive to changes in physical form parameters such as temperature-related deformations, mirror structure, piston position and detector alignment. Changes in these parameters significantly degrade image quality and often limit the performance of the system. A fundamental new technology called Wavefront Coding has been successfully demonstrated via simulations for large space-based imaging systems that promise to surpass the performance attained by traditional optical designs. Wavefront Coding uses specialized aspheric optics and signal processing of the detected image to correct defocus-like aberrations thereby enabling a new paradigm in aberration balancing for telescope systems. Wavefront Coding can provide dramatic new mission capabilities by allowing space-based imaging systems that are simpler, lighter, and cheaper, while also providing high quality imagery in dynamic environments that are difficult or impossible to image in with traditional imaging systems. As an example two systems are presented that allow the telescope to repoint the boresight through the actuation of the primary segments or through the use of a scan mirror. Traditional systems with the same goal of repointing the boresight historically have not been feasible due to either the increased error space or due to constraints on system cost and complexity.

Modeling of Wavefront Coded Imaging Systems

Wavefront Coded imaging systems are jointly optimized optical and digital imaging systems that can increase the performance and/or reduce the cost of modern imaging systems by reducing the effects of aberrations. Aberrations that can be controlled through Wavefront Coding include misfocus, astigmatism, field curvature, chromatic aberration, temperature related misfocus, and assembly related misfocus. The design and simulation of these systems are based on a model that describes all of the important aspects of the optics, detector, and digital processing being used. These models allow theoretical calculation of ideal MTFs and signal processing related parameters for new systems. These parameters are explored for extended depth of field, field curvature, and temperature related misfocus effects.

Reducing size, weight, and cost in a LWIR imaging system with wavefront coding

By jointly optimizing the design of optics, mechanics, and electronics systems with reduced size, weight, and cost can be realized. This joint optimization acts to increase the system trade-space compared to systems that optimize each component separately. Increasing the size of the system trade-space allows highly customized system design. An example of joint optimization is given for a LWIR imaging system with a conformal first surface. This example demonstrates an approximately 50% reduction in size, weight, and cost compared to acceptable traditional system solutions.

Design and optimization of computational imaging systems

A new methodology, called Wavefront Coding, allows the joint optimization of optics, mechanics, detection and signal processing of computational imaging systems. This methodology gives the system designer access to a large design trade space. This trade space can be exploited to enable the design of imaging systems that can image with high quality, with fewer physical components, lighter weight, and less cost compared to traditional optics. This methodology is described through an example conformal single lens IR imaging system. The example system demonstrates a 50% reduction in physical components, and an approximate 45% reduction in weight compared to a traditional two lens system.

Increasing the depth of field in an LWIR system for improved object identification

In a long wave infrared (LWIR) system there is the need to capture the maximum amount of information of objects over a broad volume for the identification and classification by the human or machine observer. In a traditional imaging system the optics limit the capture of this information to a narrow object volume. This limitation can hinder the observers ability to navigate and/or identify friend or foe in combat or civilian operations. By giving the observer a larger volume of clear imagery their ability to perform will drastically improve. The system presented allows the efficient capture of object information over a broad volume and is enabled by a technology called Wavefront Coding. A Wavefront Coded system employs the joint optimization of the optics, detection and signal processing. Through a specialized design of the system’s optical phase, the system becomes invariant to the aberrations that traditionally limit the effective volume of clear imagery. In the process of becoming invariant, the specialized phase creates a uniform blur across the detected image. Signal processing is applied to remove the blur, resulting in a high quality image. A device specific noise model is presented that was developed for the optimization and accurate simulation of the system. Additionally, still images taken from a video feed from the as-built system are shown, allowing the side by side comparison of a Wavefront Coded and traditional imaging system.

Digital imaging system design and trade space analysis

Designers of advanced digital imaging systems are frequently challenged with considering not only the optics and sensor, but also the effects of image processing in the selection of the best architecture to meet their system objectives. Leveraging the image processing degree of freedom presents a considerable opportunity if one incorporates system-level metrics in the design and optimization process. Including the image processing degree of freedom also significantly expands the set of solutions and enables different trades of performance, cost, size, weight, and power. Here, we demonstrate the opportunity available to the system designer by exploring the design of a wide angle system intended to maximize a system-level human visual performance metric. The resulting system solutions span a range of optical, optomechanical, and signal processing complexity and show systems with a wide range of size and cost.

IR imaging system with decreased hyperfocal distance

A long wave infrared (LWIR) computational imaging system has been designed and fabricated that has a decreased hyperfocal distance compared to traditional optics. Through the combination of aspheric optics and signal processing the near point with clear imagery has been reduced from 50m to less than 10m. Both systems deliver high quality imaging when the object is at infinity. The decrease in the hyperfocal distance was realized though the use of Wavefront Coding, a technology where all system components are jointly optimized. The system components include the optics, detector and signal processing. System optimization is used with optical/digital constraints such as manufacturability, cost, signal processing architecture, FPA characteristics, etc. Through a special design of the system’s optical phase, the system becomes invariant to the aberrations that traditionally limit the effective operational range. In the process of becoming invariant, the specialized phase creates a uniform blur across the detected image. Signal processing is applied to remove the blur, resulting in a high quality image. In this paper imagery from the Wavefront Coded system is described and compared to traditional imagery.

Computational imaging: beyond the limits imposed by lenses (Conference Presentation)

This Conference Presentation, “Computational imaging: beyond the limits imposed by lenses,” was recorded at SPIE Commercial + Scientific Sensing and Imaging 2017 held in Anaheim, California, United States.