Jeremy Murray-Krezan

Enhancement of imagery of objects with highly dynamic brightness and large rotational motion

We report on application of multi-frame super-resolution (SR) to sampling limited imagery that models space objects (SOs). The difficulties of multi-frame image processing of SOs include abrupt illumination changes and complex in scene SO motion. These conditions adversely affect the accuracy of motion estimation necessary for resolution enhancement. We analyze the motion estimation errors from the standpoint of an optical flow (OF) interpolation error metric and show dependence of the object tracking accuracy on brightness changes and on the pixel displacement values between subsequent images. Despite inaccuracies of motion estimation, we demonstrate spatial acuity enhancement of the pixel limited resolution of model SO motion imagery by applying a SR algorithm that accounts for OF errors. In addition to visual inspection, image resolution improvement attained in the experiments is assessed quantitatively; a 1.8× resolution enhancement is demonstrated.

Geometric super-resolution via log-polar FFT image registration and variable pixel linear reconstruction

Various image de-aliasing techniques and algorithms have been developed to improve the resolution of pixel-limited imagery acquired by an optical system having an undersampled point spread function. These techniques are sometimes referred to as multi-frame or geometric super-resolution, and are valuable tools because they maximize the imaging utility of current and legacy focal plane array (FPA) technology. This is especially true for infrared FPAs which tend to have larger pixels as compared to visible sensors. Geometric super-resolution relies on knowledge of subpixel frame-toframe motion, which is used to assemble a set of low-resolution frames into one or more high-resolution (HR) frames. Log-polar FFT image registration provides a straightforward and relatively fast approach to estimate global affine motion, including translation, rotation, and uniform scale changes. This technique is also readily extended to provide subpixel translation estimates, and is explored for its potential combination with variable pixel linear reconstruction (VPLR) to apportion a sequence of LR frames onto a HR grid. The VPLR algorithm created for this work is described, and HR image reconstruction is demonstrated using calibrated 1/4 pixel microscan data. The HR image resulting from VPLR is also enhanced using Lucy-Richardson deconvolution to mitigate blurring effects due to the pixel spread function. To address non-stationary scenes, image warping, and variable lighting conditions, optical flow is also investigated for its potential to provide subpixel motion information. Initial results demonstrate that the particular optical flow technique studied is able to estimate shifts down to nearly 1/10th of a pixel, and possibly smaller. Algorithm performance is demonstrated and explored using laboratory data from visible cameras.

A study of image quality for imagery generated by standard and hybrid intensity interferometers

Phase retrieval is explored for image reconstruction using outputs from both a simulated intensity interferometer (II) and a hybrid system that combines the II outputs with partially resolved imagery from a traditional imaging telescope. Partially resolved imagery provides an additional constraint for the phase retrieval process, as well as an improved starting point for the algorithm. The benefits of this additional a priori information are explored, and when combined with standard constraints such as positivity and compact support include faster convergence, increased sensitivity, and improved image quality.

Effects of aberrations on image reconstruction of data from hybrid intensity interferometers

Intensity interferometery (II) holds tremendous potential for remote sensing of space objects. We investigate the properties of a hybrid intensity interferometer concept where information from an II is fused with information from a traditional imaging telescope. Although not an imager, hybrid intensity interferometery measurements can be used to reconstruct an image. In previous work we investigated the effects of poor SNR on this image formation process. In this work, we go beyond the obviously deleterious effects of SNR, to investigate reconstructed image quality as a function of the chosen support constraint, and the resultant image quality issues. The benefits to fusion of assumed perfect-yet-partial a priori information with traditional intensity interferometery measurements are explored and shown to result in increased sensitivity and improved reconstructed-image quality.

Adaption from LWIR to visible wavebands of methods to describe the population of GEO belt debris

Prior efforts to characterize the number of GEO belt debris objects by statistically analyzing the distribution of debris as a function of size have relied on techniques unique to infrared measurements of the debris. Specifically the infrared measurement techniques permitted inference of the characteristic size of the debris. This report describes a method to adapt the previous techniques and measurements to visible wavebands. Results will be presented using data from a NASA optical, visible band survey of objects near the geosynchronous orbit, GEO belt. This survey used the University of Michigans 0.6-m Curtis-Schmidt telescope, Michigan Orbital DEbris Survey Telescope (MODEST), located at Cerro Tololo Inter-American Observatory in Chile. The system is equipped with a scanning CCD with a field of view of 1.6°×1.6°, and can detect objects smaller than 20 cm diameter at GEO.

Sensitivity analysis of a space-based multi-band infrared imager for GEO belt debris study

Thousands of space objects in the Earth orbital-region known as the GEO belt are categorized as debris. Relatively little is known about the thousands of space debris objects. Remote sensing techniques offer the only viable opportunity to learn more about these objects. In this paper an analysis is performed for observations using a hypothetical space-based multi-band infrared instrument to measure characteristics of GEO belt space debris. The purpose of this study is to understand the limitations of such an instrument and sensing modality for studying GEO belt space debris. Although certain aspects of this study are analytical, the results are anchored with results from the NASA-WISE experiments.

The Joint Space Operations Center Mission System and the Advanced Research, Collaboration, and Application Development Environment Status Update 2016

The Joint Space Operations Center (JSpOC) Mission System (JMS) is a service-oriented architecture (SOA) infrastructure with increased process automation and improved tools to enhance Space Situational Awareness (SSA) performed at the US-led JSpOC. The Advanced Research, Collaboration, and Application Development Environment (ARCADE) is a test-bed maintained and operated by the Air Force to (1) serve as a centralized test-bed for all research and development activities related to JMS applications, including algorithm development, data source exposure, service orchestration, and software services, and provide developers reciprocal access to relevant tools and data to accelerate technology development, (2) allow the JMS program to communicate user capability priorities and requirements to developers, (3) provide the JMS program with access to state-of-the-art research, development, and computing capabilities, and (4) support JMS Program Office-led market research efforts by identifying outstanding performers that are available to shepherd into the formal transition process. In this paper we will share with the international remote sensing community some of the recent JMS and ARCADE developments that may contribute to greater SSA at the JSpOC in the future, and share technical areas still in great need.

Distributions of debris as measured by the NASA-WISE instrument

From December 2009 thru 2011 the NASA Wide-Field Infrared Survey Explorer (WISE) gathered radiometrically exquisite measurements of debris in near Earth orbits, adding substantially to the current catalog of known debris. Assuming grey-body emissivity, the apparent size of debris objects may be inferred from that data. This report describes a general model for debris size distributed near the GEO belt. Linear and nonlinear regression models were fit to data from the WISE orbital debris catalog. Using those results we estimate the sensitivity of the instrument to detection of small debris objects near the GEO belt.

Situational awareness investigation using tracking and enhancement of imagery with highly dynamic lighting conditions

We report on the application of Optical Flow (OF) and state-of-the art multi-frame Super-Resolution (SR) algorithms to imagery that models space objects (SOs). Specifically, we demonstrate the ability to track SOs through sequences consisting of tens of images using different OF algorithms and show dependence of the tracking accuracy on illumination condition changes and on the values of pixel displacements between neighboring images. Additionally, we demonstrate spatial acuity enhancement of the pixel limited resolution of SO motion imagery by applying a novel SR algorithm accounting for OF errors.

A Study of Image Reconstruction Algorithms for Hybrid Intensity Interferometers

Phase retrieval is explored for image reconstruction using outputs from both a simulated intensity interferometer (II) and a hybrid system that combines the II outputs with partially resolved imagery from a traditional imaging telescope. Partially resolved imagery provides an additional constraint for the iterative phase retrieval process, as well as an improved starting point. The benefits of this additional a priori information are explored and include lower residual phase error for SNR values above 0.01, increased sensitivity, and improved image quality. Results are also presented for image reconstruction from II measurements alone, via current state-of-the-art phase retrieval techniques. These results are based on the standard hybrid input-output (HIO) algorithm, as well as a recent enhancement to HIO that optimizes step lengths in addition to step directions. The additional step length optimization yields a reduction in residual phase error, but only for SNR values greater than about 10. Image quality for all algorithms studied is quite good for SNR≥10, but it should be noted that the studied phase-recovery techniques yield useful information even for SNRs that are much lower.