Skip to main content

Knight Vision Lab

About
Research
People
Publications

Knight Vision Lab (KVL)

The Knight Vision Lab conducts pioneering research on infrared imaging technologies spanning materials and components to systems and applications. We have three primary activities:

  1. Metasurface aberration correctors to improve performance, size and cost of infrared lenses. 
  2. Vision-based navigation using imagery to determine geolocation.
  3. Sensing technologies from small UASs.
We are looking for post-doctoral researchers to join our team! Applicants must meet government requirements on a project-dependent basis prior to joining the team. Contact Prof. Renshaw for more information.
KVL Logo

KVL & IR Systems Group at SPIE DCS 2023

News & Info

  • Conducted remote sensing data collection at Eglin AFB with ARL and Chicken Little
  • Started round 2 for python detection – we are now building a drone-based system
  • May: KVL presents 5 papers at SPIE Defense and Commercial Sensing Symposium
  • Alex graduates with his B.S. in ECE (Surprise!)
  • Completed field test at Big Oaks Ranch for VISNAV and MUAS projects  (see video below)
  • Hank interns at Metalenz (summer)
  • Li interns at Amazon, Machine Vision and Optical Engineering team (Fall)
  • Congraduations to Pooya, Sajad and Zhao for defending their PhD theses this spring!
  • April: 5 papers presented at SPIE Defense and Commercial Sensing – a record for KVL
  • Pooya and Sajad’s paper on visible light communications came out in JLT
  • Ko-Han’s metasurface lens paper in Opt. Exp. featured as an Editor’s Pick
  • July: 4 KVL members concluded a successful week of data collection in Memphis with collaborators
  • KVL leads a $4M award to research targeting technologies for high-energy lasers
  • KVL welcomes two new members, Oles and Eunmo, to do research in active targeting systems
  • Congratulations to Robert for defending his PhD thesis this Fall!
  • Dec: 6 KVL members participated in a data collection event in the Santa Rita Experimental Range near Tucson. 
  • Heath successfully defended his thesis, congratulations Dr. Gemar!
  • TFO Lab changes name to Knight Vision Lab to better reflect our research focus on imaging technologies.
  • TFO spearheads a collaboration on vision-based navigation [read more]
  • Heath’s paper on MWIR nanoaperture filters published in Opt. Mat. Exp.
  • Jen’s python detection work published in App. Opt. was featured in local [1,2] and national news [3,4]
  • May 16: TFO summer party celebrates an end to COVID isolation
  • Cesar wraps up his senior design and research thesis to graduate with honors!
  • Robert presents thermal contrast enhancement using multiple thermal bands at SPIE DCS
  • Zhao’s Volumetric Imaging Efficiency (VIE) paper published in Opt. Exp.
  • COVID happened = 2020 🙁
  • Cesar wins best poster at the UofA Winter School of Optics
  • Cesar wins Distinguished Undergraduate Research Award
  • Sajad and Pooya present VLC Transmitter at MobiCom/LIoT
  • Sajad presents PICO Array development at CLEO 
  • The TFO group expands: welcome new team members!
Sajad wins best poster at 2019 IEEE Summer Topical Symposium
  • Cesar receives Most Outstanding Summer Researcher from AFRL. 
  • Zhao’s JAP paper receives editor’s pick and is featured in Scilights.
  • Sajad wins best poster at the IEEE Summer Topical meeting for “Photonic Integrated Circuit Outcoupling (PICO) Arrays for Free-Space Optical Communications.”
  • Sajad is selected for a summer internship at IMEC-Florida. 
  • Sajad wins best poster at the Industrial Affiliates Symposium for “Camera/Inverse-Camera System for Free-Space Optical Communications.”
  • Cesar is accepted for a summer internship at AFRL. 
  • Sajad presents an Inverse-Camera System for Optical Wireless Communications at Frontiers in Optics 
  • Dr. Renshaw presents a switchable organic photodiode at OSA Imaging Congress 
  • Dr. Renshaw awarded AFRL Summer Faculty Fellowship 
  • Zhao presents a poster on curved sensor fabrication at SPIE Defense and Commercial Sensing 
  • Angstrom deposition tool is installed; first films grown and OPD/OLED devices fabricated
  • TFO Lab is completed! 

Current Research

Drone-based Remote Sensing

Rapid proliferation of Class 2 drones (<55 lb) presents many new opportunities for remote sensing. We are working with U of Memphis, U of Arizona and Army Research Lab to develop cooperative remote sensing capabilities using multiple drones to search or map large areas in an coordinated manner. We are also deploying numerous sensing modalities onto small drones for various sensing applications.

Volumetric Imaging Efficiency (VIE)

Major investments are pouring into a wide variety of optical materials and lens technologies such as metamaterials, free-form surfaces, printed or molded optical glass and plastics, gradient index materials and manufacturing curved image sensors. These all seek to achieve the same objective – make optical systems (and usually imaging systems) perform better, cost less or become smaller. But which technology stands to provide the best improvement or the best bang for your research buck? We developed the VIE metric in an attempt to answer that question from a technology-agnostic perspective. The VIE is a measure of the resolution density of an imaging optic compared against the most dense system possible based on fundamental limits of diffraction. 

We collected >2800 lens designs and showed an empirical limit to the VIE of conventional imaging systems – using bulk optics imaging onto flat sensors. The limiting VIE decreases exponentially with FOV. We show examples of bulk lenses imaging onto curved sensors and metasurface lenses that surpass conventional systems by ~100x. These technologies particularly excel in wide angle applications where conventional lenses grow to become very bulky. 

Volumetric Channel Density of various lenses plotted along with the fundamental limits based on diffraction-limited imaging onto a flat sensors (blue circles) and onto a curved sensor (red squares)
Volumetric Channel Density of various lenses plotted along with the fundamental limits based on diffraction-limited imaging onto a flat sensors (blue circles) and onto a curved sensor (red squares)
VIE vs FOV for >2800 lenses. Efficiency of multi-metasurface (MMS) lenses are plotted as curved lines. Short focal length MMSs with 2 or more surfaces can surpass the limits of conventional lenses
VIE vs FOV for >2800 lenses. Efficiency of multi-metasurface (MMS) lenses are plotted as curved lines. Short focal length MMSs with 2 or more surfaces can surpass the limits of conventional lenses
VIE vs Field-of-view for library of conventional lenses using bulk optics. VIE decreases exponentially when imaging onto flat sensors (numbered points); imaging onto a curved surface enables high efficiency at wide angles (crescents)
VIE vs Field-of-view for library of conventional lenses using bulk optics. VIE decreases exponentially when imaging onto flat sensors (numbered points); imaging onto a curved surface enables high efficiency at wide angles (crescents)
Previous
Next
Multi-Metasurface Lenses

Metasurface lenses use sub-wavelength, nanostructured scattering features to to control light in new ways. For example, flat lenses mimic the phase delay of a conventional, bulk lens by engineering the effective index to give the same profile across a planar surface. Flat singlets, doublets and achromats have already been fabricated and demonstrated in laboratory camera systems. Challenges abound related to scattering efficiency, dispersive characteristics and scaling challenges. We are working to address MS scaling by combining bulk lenses for primary power and MS lenses for aberration correction. This work includes modelling and simulation, optical design, nanofabrication in the cleanroom and optical test and characterization. Multiscale modelling and simulation spans full-wave FDTD simulations in Lumerical to geometric ray tracing in Zemax with aid from inverse design optimization for design down to individual meta-atom placements across the surface.  

Full-wave simulations of blazed grating structures capture the transmission and diffraction efficiency of metasurface optics beyond the local uniformity approximation.
Full-wave simulations of blazed grating structures capture the transmission and diffraction efficiency of metasurface optics beyond the local uniformity approximation.
Developing tools and methods to design metasurface aberration correctors that work with bulk optics to improve imaging performance while reducing size.
Developing tools and methods to design metasurface aberration correctors that work with bulk optics to improve imaging performance while reducing size.
Example of point-spread functions with and without the metasurface aberration correctors.
Example of point-spread functions with and without the metasurface aberration correctors.
Previous
Next
Curved Image Relays based on
MWIR/LWIR coherent fiber bundles

The DARPA SCENICC program demonstrated viability of curved image relays to enable compact, wide-angle imaging systems in the visible. We are collaborating with experts in chalcogenide glass growth and fiber drawing (all at CREOL) to manufacture high-resolution and large format coherent fiber bundles for thermal imagers in the midwave (MWIR) and longwave (LWIR) infrared bands. We are fabricating these novel optics to relay curved images to flat sensors to enable a new breed of compact, wide-angle and high-resolution thermal imagers. 

We are investigating microstructured and step-index fibers for MWIR imaging bundles. (top) Imaging fiber bundle for visible fibers used by S. Karbasi, et al., to create compact, wide FOV imagers. (bottom) Silica-based MWIR imaging fiber bundle designs based on anti-resonant reflective optical waveguides (ARROW).
We are investigating microstructured and step-index fibers for MWIR imaging bundles. (top) Imaging fiber bundle for visible fibers used by S. Karbasi, et al., to create compact, wide FOV imagers. (bottom) Silica-based MWIR imaging fiber bundle designs based on anti-resonant reflective optical waveguides (ARROW).
Fiber pre-form and drawing process using tabletop tower in collaboration with Dr. Kaufman and Dr. Tan
Fiber pre-form and drawing process using tabletop tower in collaboration with Dr. Kaufman and Dr. Tan
Previous
Next
Python Detection System

Burmese pythons are invading the everglades and destroying the natural ecosystem. We are working with the Florida Fish and Wildlife Commission (FFWC) to develop a near-infrared python detection system comprised of a multi-camera array and automated detection algorithms. The system is in development and we are actively working with the FFWC and contracted hunters to test the system effectiveness. 

Preliminary data collection for proof-of-concept
Preliminary data collection for proof-of-concept
Hyperspectral characterization of pythons and background samples typically found in the everglades
Hyperspectral characterization of pythons and background samples typically found in the everglades
Comparison of visible verse near-infrared imagery used in perception experiments.
Comparison of visible verse near-infrared imagery used in perception experiments.
A truck mounted, multi-camera detection system build for the Florida FIsh and Wildlife Conservation Commission.
A truck mounted, multi-camera detection system build for the Florida FIsh and Wildlife Conservation Commission.
The near-infrared system enhances contrast of pythons against their surroundings making them easier to detect.
The near-infrared system enhances contrast of pythons against their surroundings making them easier to detect.
Previous
Next
Vision-Based Navigation

GPS has revolutionized life and technology but what happens when it fails or is jammed? We are developing vision-based navigation technologies for ground vehicles that use imagery and geospatial data to estimate location. Fusing thermal infrared imagery with other sensors provides a robust navigation solution day or night to augment traditional GPS. 

Comparison of tower imagery using visible sensor and a longwave infrared sensor during the day and at night.
Comparison of tower imagery using visible sensor and a longwave infrared sensor during the day and at night.
Imagery from onboard cameras can be used to estimate position by recognizing features in the scene.
Imagery from onboard cameras can be used to estimate position by recognizing features in the scene.
Diverse geospatial datasets are available to aid vision-based navigation.
Diverse geospatial datasets are available to aid vision-based navigation.
Vehicle testbed equipped with sensors, cameras, and electronics for data collection and experimentation.
Vehicle testbed equipped with sensors, cameras, and electronics for data collection and experimentation.
Gimballed, multi-camera system installed on the Jeep during a data collection event.
Gimballed, multi-camera system installed on the Jeep during a data collection event.
A checkerboard target being used to calibrate distortion of an infrared imager.
A checkerboard target being used to calibrate distortion of an infrared imager.
Previous
Next
Imaging-Based Beam Steering

We have introduced a new beam-steering mechanism that utilizes the passive mapping between spatial and angular coordinates provided by an imaging optic. This can provide high-resolution beam steering over a wide field-of-regard with no moving parts in a compact and low-power system; overcoming many of the problems inherent in conventional beam-steering approaches using moving mirrors, phased-arrays or spatial light modulators.  

Schematic, model and experimental setup using an organic LED display coupled to a 50mm focal length photographic lens to demonstrate imaging-based beam steering (IBBS).
Schematic, model and experimental setup using an organic LED display coupled to a 50mm focal length photographic lens to demonstrate imaging-based beam steering (IBBS).
(top) Beam profile measurements near the lens and sufficiently far that we observe the microstructured irradiance pattern of the 200micron spot on the OLED display. (bottom) Experimentally measured beam locations across the lenses 30 degree FOV yield RMS pointing error of ~5mrad. Beam radius verse distance from the transmitter shows ~1.25mrad beam divergence.
(top) Beam profile measurements near the lens and sufficiently far that we observe the microstructured irradiance pattern of the 200micron spot on the OLED display. (bottom) Experimentally measured beam locations across the lenses 30 degree FOV yield RMS pointing error of ~5mrad. Beam radius verse distance from the transmitter shows ~1.25mrad beam divergence.
Previous
Next

People

Principle Investigator

C. Kyle Renshaw

Dr. Kyle Renshaw directs the Knight Vision Lab. He is an assistant professor of optics with joint appointments in the department of physics and electrical and computer engineering.

Research Scientist

Jeremy Mares

Dr. Jeremy Mares is a Research Scientist in KVL specializing in imaging systems and related technologies. 

Principle Collaborators

Ronald-Driggers-683x1024

Dr. Ron Driggers directs the Infrared Systems Group at the Univ. of Arizona and collaborates with KVL broadly across applied imaging and infrared technology developments.

headshot_jacobs2

Dr. Eddie Jacobs is a Professor of Electrical Engineering at the University of Memphis. His team spearheads our joint effort in remote sensing using drones. 

Graduate Students

Undergraduate Researchers

Group Photo - Spring 2021

TFO Group Photo May 2021

Alumni

PhD

Zhao Ma, Optics Ph.D., Summer 2022
Heath Gemar, Optics Ph.D., Fall 2021
Robert Grimming, Optics Ph.D., Fall 2022
Pooya Nabavi, Electrical Engineering Ph.D., Spring 2022
Sajad Saghaye-Polkoo, Physics Ph.D., Spring 2022

MS

Donald Hoff, Optics M.S., Fall 2021
Jennifer Kassel, Optics M.S., Fall 2017

BS

Cesar Lopez-Zelaya, Photonic Science & Engineering B.S., Spring 2021
Austin Brigham, Photonic Science & Engineering B.S., Spring 2022
Austin Horvath, Photonic Science & Engineering B.S., Spring 2022

Publications

Journal Articles

  1. J. Follansbee, D. Burrell, O. Furxhi, C. K. Renshaw, J. Lund and R. Driggers “Target acquisition performance comparison of active continuous-wave and range-gated imaging systems at 1.6 and 2.1 µm” Optical Engineering 62(9), 094107 (2023)
  2. R. Grimming, O. Furxhi, R. Driggers and K. Renshaw “Multiband longwave infrared reflectance removal using blackbody channel prior” Optical Engineering 62(3), 033101 (2023) (2023)
  3. K.H. Shih and C.K. Renshaw “Broadband metasurface aberration correctors for hybrid meta/refractive MWIR lenses” Optics Express, 30(16), pp. 28438-28453 (2022)
  4. Shih, KH; Renshaw, CK “Broadband metasurface aberration correctors for hybrid meta/refractive MWIR lenses: publisher's note (vol 30, pg 28438, 2022)” Optics Express, 30(17), pp. 31518-31518 (2022)
  5. P. Nabavi, S. S. Polkoo, M. Yuksel and C. K. Renshaw “A Multi-LED Dome Bulb Prototype for Dense Visible Light Communication Networks” Journal of Lightwave Technology, Early Access (2022)
  6. H. Gemar, M.K. Yetzbacher, R.G. Driggers and C.K. Renshaw “Near-field coupling of absorbing material to subwavelength cavities” Optical Materials Express, 11(8), pp. 2576-2586 (2021)
  7. J. Hewitt, O. Furxhi, C.K. Renshaw and R. Driggers “Detection of Burmese pythons in the near infrared vs. visible band” Applied Optics, 60(17), pp. 5066-5073 (2021)
  8. Z. Ma, K.H. Shih, C. Lopez-Zelaya and C.K. Renshaw “Volumetric Imaging Efficiency: the Fundamental Limit to Compactness of Imaging Systems” Optics Express, 29(3), pp. 3173-3192 (2021)
  9. C.Y. Zhang, J.X. Li, A. Belianinov, Z. Ma, C.K. Renshaw and R.M. Gelfand “Nanoaperture fabrication in ultra-smooth single-grain gold films with helium ion beam lithography” Nanotechnology, 31(46), A. 465302 (2020)
  10. M. Teng, A. Honardoost, Y. Alahmadi, S. S. Polkoo, K. Kojima, H. Wen, C.K. Renshaw , P. LiKamWa, G. F. Li, S. Fathpour, R. Safian, and L. M. Zhuang “Miniaturized Silicon Photonics Devices for Integrated Optical Signal Processors” IEEE/OSA Journal of Lightwave Technology, vol. 38, pp. 6-17, January 2020 (INVITED). (2020)
  11. Z. Ma and C.K. Renshaw “Organic photodetectors with frustrated charge transport for small-pitch image sensors” Journal of Applied Physics, 126(4), 045501 (2019)
  12. S.S. Polkoo and C.K. Renshaw “Imaging-based beam steering for free-space optical communication” Applied Optics, 58(13), pp. D12-D21 (2019)
  13. C. K. Renshaw and S. R. Forrest “Excited State and Charge Dynamics of Hybrid Organic/Inorganic Junctions. I. Theory” Phys. Rev. B 90, 045302 (2014) (2014)
  14. A. Panda, C. K. Renshaw, A. Oskooi, K. Lee, and S. R. Forrest “Excited State and Charge Dynamics of Hybrid Organic/Inorganic Junctions. II. Experiment” Phys. Rev. B 90, 045303 (2014) (2014)
  15. B. E. Lassiter, C. K. Renshaw and S. R. Forrest “Understanding Tandem Organic Photovoltaic Cell Performance” J. Apply. Phys. 113, 214505 (2013) (2013)
  16. C. K. Renshaw, J. D. Zimmerman, B. E. Lassiter, and S. R. Forrest “Photoconductivity in Organic Photovoltaics” Phys. Rev. B 86, 085324 (2012) (2012)
  17. J. D. Zimmerman, X. Xiao, C. K. Renshaw, S. Wang, V. V. Diev, M. E. Thompson, and S. R. Forrest “Independent Control of Bulk and Interfacial Morphologies of Small Molecular Weight Organic Heterojunction Solar Cells” Nano Lett. 12, 4366 (2012) (2012)
  18. C. K. Renshaw, C. Schlenker, M. E. Thompson, and S. R. Forrest “Reciprocal Carrier Collection in Organic Photovoltaics” Phys. Rev. B 84, 045315 (2011) (2011)
  19. N. Li, K. Lee, C. K. Renshaw, X. Xiao, and S. R. Forrest “Improved Power Conversion Efficiency of InP Solar Cells Using Organic Window Layers” Appl. Phys. Lett. 98, 053504 (2011) (2011)
  20. K. Lee, K. Shiu, J. D. Zimmerman, C. K. Renshaw, and S. R. Forrest “Multiple Growths of Epitaxial Lift-off Solar Cells from a Single InP Substrate” Appl. Phys. Lett. 97, 101107 (2010) (2010)
  21. B. E. Lassiter, R. R. Lunt, C. K. Renshaw, and S. R. Forrest “Structural Templating of Multiple Polycrystalline Layers in Organic Photovoltaic Cells” Optics Express 18, No. 103, A444 (2010) (2010)
  22. G. Wei, S. Wang, K. Renshaw, M. E. Thompson, and S. R. Forrest “Solution-Processed Squaraine Bulk Heterojunction Photovoltaic Cells” ACS Nano 4, No. 4, 1927 (2010) (2010)
  23. C. K. Renshaw, X. Xu, and S. R. Forrest “A Monolithically Integrated Organic Photodetector and Thin Film Transistor” Org. Elect. 11, 175 (2010) (2010)
  24. M. S. Arnold, J. D. Zimmerman, C. K. Renshaw, X. Xu, R. R. Lunt, C. M. Austin, and S. R. Forrest “Broad Spectral Response Using Carbon Nanotube/Organic Semiconductor/C60 Photodetectors” Nano Lett. 9, No. 9, 3354 (2009) (2009)
  25. S. Ghosh, A. R. Bhagwat, C. K. Renshaw, S. Goh, and A. L. Gaeta “Low-Light-Level Optical Interactions with Rubidium Vapor in a Photonic Band-Gap Fiber” Phys. Rev. Lett. 97, 023603 (2006) (2006)

Conference Presentations

  1. E. L. Jacobs, O. Furxhi, K. Renshaw, R. Driggers and J. Conroy “Multiple UAS/Multiple Sensors for Intelligence, Surveillance, and Reconnaisance” 2023 IEEE Research and Applications of Photonics in Defense Conference (RAPID), 2021, pp. 1-2 (2023)
  2. R. Cavanaugh, E. Chau, P. Leslie, L. Wiley, E. L. Jacobs, K. Renshaw, R. Driggers and J. K. Conroy “Cell tower detection in the VIS, SWIR and LWIR bands” Proc. SPIE Defense and Commercial Sensing, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIV, 12533-11 (2023)
  3. T. P. Watson, K. McKenzie, A. Robinson, K. Renshaw, R. Driggers, E. L. Jacobs and J. Conroy “Evaluation of aerial real-time RX anomaly detection” Proc. SPIE Defense and Commercial Sensing, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXIX, 12519-40 (2023)
  4. K. Shih and C. K. Renshaw “Metasurface hybrid lens inverse design with diffractive/refractive co-optimization” Proc. SPIE Defense and Commercial Sensing, Advanced Optics for Imaging Applications: UV through LWIR VIII, 12530-21 (2023)
  5. L. Zhang, M. Martino, A. Irwin, J. Mares, O. Furxhi and C. K. Renshaw “Modelling performance of AI/ML-based tower localization in thermal imagery” Proc. SPIE Defense and Commercial Sensing, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIV, 12533-4 (2023)
  6. W. Chen and C. K. Renshaw “Monochrome metasurface lens design for optical wireless transceivers” Proc. SPIE Defense and Commercial Sensing, Advanced Optics for Imaging Applications: UV through LWIR VIII, 12530-18 (2023)
  7. A. J. Ramirez, K. Renshaw, R. Driggers, J. Conroy and E. L. Jacobs “Motion blur modeling for multi-roto and fixed wing UAVs” Proc. SPIE Defense and Commercial Sensing, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIV, 12533-16 (2023)
  8. J. Mares, M. Martino, A. Irwin, L. Zhang, O. Furxhi and C. K. Renshaw “Vehicle self-localization in GPS-denied zones by multi-band imaging and analysis of prominent scene features” Proc. SPIE Defense and Commercial Sensing, Infrared Technology and Applications XLIX, 12534-56 (2023)
  9. A. Irwin, J. Mares, M. Martino, L. Zhang, O. Furxhi, E. Jacobs, R. Driggers and C. K. Renshaw “Vehicle testbed for multispectral imaging and vision-based geolocation” Proc. SPIE Defense and Commercial Sensing, Infrared Technology and Applications XLIX, 12534-55 (2023)
  10. Nabavi, P (Nabavi, Pooya) [1] , [2] ; Yuksel, M (Yuksel, Murat) [1] , [2] ; Renshaw, CK (Renshaw, Christopher Kyle) [1] , [2] , [3] “Performance Analysis of Multi-Input Single-Output Links in Dense VLC Networks” 2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022)pp. 1296-1301 (2023)
  11. P. Nabavi, M. Yuksel and C. K. Renshaw “Performance analysis of multi-input single-output links in dense VLC networks” IEEE Global Communications Conference, 1296 (2022) (2022)
  12. C. K. Renshaw, J. Hewitt, R. Grimming and R. G. Driggers “Sensor optimization for image-based geolocation” OSA Imaging and Applied Optics Congress 2022, JF2D.6 (2022)
  13. C. K. Renshaw, J. Hewitt, L. Zhang, I. Tanner, M. Behnke, A. Mahalanobis, T. Watson, E. Jacobs and R. Driggers “Development of a near-infrared (NIR) python detection system” 2022 Everglades Invasive Species Summit (2022)
  14. L. Zhang, C. Lopez-Zelaya, A. Badillo, F. Tan, J. Kaufman and C. K. Renshaw “Hybrid chalcogenide/polymer coherent fiber bundles for MWIR imaging” Proc. SPIE Defense and Commercial Sensing, Advanced Optics for Imaging Applications: UV through LWIR VII, 12103-2 (2022)
  15. C. Revello, R. Driggers, D. Brady and C. K. Renshaw “Large area coverage using drone mounted multi-camera systems” Proc. SPIE Defense and Commercial Sensing, Infrared Imaging Systems: Design, Analysis, Modeling and Testing XXXIII, 12106-7 (2022)
  16. K. Shih and C. K. Renshaw “Low-dispersion nanohole metasurfaces for refractive-diffractive hybrid lens design in MWIR” Proc. SPIE Defense and Commercial Sensing, Advanced Optics for Imaging Applications: UV through LWIR VII, 12103-3 (2022)
  17. Z. Ma and C. K. Renshaw “Organic photodetector charge blocking mechanism by numerical simulation” Proc. SPIE Defense and Commercial Sensing, Image Sensing Technologies: Materials, Devices, Systems and Applications IX, 12091-14 (2022)
  18. J. Hewitt, C. K. Renshaw, O. Furxhi, L. Zhang and R. Driggers “Sensor optimization of camera direction for time-limited search performance” Proc. SPIE Defense and Commercial Sensing, Infrared Imaging Systems: Design, Analysis, Modeling and Testing XXXIII, 12106-3 (2022)
  19. C. Lopez-Zelaya, L. Zhang, A. Badillo, F. Tan, J. Kaufman and C. K. Renshaw “Hybrid Chalcogenide/Polymer Coherent Fiber Bundles for MWIR Image Relays” 2021 IEEE Research and Applications of Photonics in Defense Conference (RAPID) (2021)
  20. J. Hewitt, C. K. Renshaw, O. Furxhi and R. Driggers “Optimizing sensor design using a time-limited search model for moving sensor” 2021 IEEE Research and Applications of Photonics in Defense (RAPID) Conference (2021)
  21. K. Shih and C. K. Renshaw “Silicon-on-insulator metasurface aberration corrector inverse design for mid-infrared imaging” 2021 IEEE Research and Applications of Photonics in Defense Conference (RAPID) (2021)
  22. C. K. Renshaw and Z. Ma “Volumetric imaging efficiency of multi-metasurface lenses” Proc. SPIE 11795, Metamaterials, Metadevices and Metasystems, 117951P (2021)
  23. R. Grimming, R. Driggers, K. Renshaw and O. Furxhi “Ground-level temperature-emissivity-based contrast enhancement with uncooled multiband LWIR cameras” Proc. SPIE 11740, Infrared Imaging Systems, 117400J (2021)
  24. S. S. Polkoo, P. Nabavi, M. Yuksel and C. K. Renshaw “Multi-LED multi-datastream dome bulb for dense visible light communication networks” 2020 LIOT: Proceedings of the Workshop on Light Up the IoT, 12 (2020) (2020)
  25. S. S. Polkoo and C. K. Renshaw “Hybrid imaging-based beam steering system using a sparse photonic integrated circuit outcoupling array” 2020 CLEO: Conference on Lasers and Electro-Optics, JTh2B.25 (2020) (2020)
  26. Z. Ma, C. Lopez-Zelaya and C. K. Renshaw “Low Volume Imaging with Metasurfaces” 2019 IEEE Research and Applications of Photonics in Defense (RAPID), TuA2 (2019) (2019)
  27. S. S. Polkoo and C. K. Renshaw “Integrated Photonic Outcoupling Array for Imaging-Based Beam Steering” 2019 IEEE Photonics Society Summer Topical Meeting, MP7 (2019) (2019)
  28. S. S. Polkoo and C. K. Renshaw “Camera and Inverse Camera System for Free-Space Optical Communications” Frontiers in Optics / Laser Science, JW4A.20 (2018) (2018)
  29. Z. Ma and C. K. Renshaw “2-Terminal Organic FPA Pixel Design for Curved Image Sensors” Imaging and Applied Optics, ITh2B.3 (2018) (2018)
  30. Z. Ma and C.K. Renshaw “Hemispherical image sensor development for wide FOV imaging” SPIE, Image Sensing Technologies: Materials, Devices, Systems, and Applications, 10656-61 (2018)