Information theoretic approach for assessing image fidelity in photon-counting arrays

The method of photon-counting integral imaging has been introduced recently for three-dimensional object sensing, visualization, recognition and classification of scenes under photon-starved conditions. This paper presents an information-theoretic model for the photon-counting imaging (PCI) method, thereby providing a rigorous foundation for the merits of PCI in terms of image fidelity. This, in turn, can facilitate our understanding of the demonstrated success of photon-counting integral imaging in compressive imaging and classification. The mutual information between the source and photon-counted images is derived in a Markov random field setting and normalized by the source-image’s entropy, yielding a fidelity metric that is between zero and unity, which respectively corresponds to complete loss of information and full preservation of information. Calculations suggest that the PCI fidelity metric increases with spatial correlation in source image, from which we infer that the PCI method is particularly effective for source images with high spatial correlation; the metric also increases with the reduction in photon-number uncertainty. As an application to the theory, an image-classification problem is considered showing a congruous relationship between the fidelity metric and classifier’s performance

Synthetic aperture single-exposure on-axis digital holography

We present a system for reconstructing single-exposure on-line (SEOL) digital holograms with improved resolution using a synthetic aperture. Several recordings are made in order to compose the synthetic aperture, shifting the camera within the hologram plane. After processing the synthetic hologram, an inverse Fresnel transformation provides an enhanced resolution reconstruction. We show that recognition capacity for high frequency details is increased. Experimental results with a test target and with a microscopic biological sample are presented. Both visualization and correlation results are reporte

Polarimetric 3D integral imaging in photon-starved conditions

We develop a method for obtaining 3D polarimetric integral images from elemental images recorded in low light illumination conditions. Since photon-counting images are very sparse, calculation of the Stokes parameters and the degree of polarization should be handled carefully. In our approach, polarimetric 3D integral images are generated using the Maximum Likelihood Estimation and subsequently reconstructed by means of a Total Variation Denoising filter. In this way, polarimetric results are comparable to those obtained in conventional illumination conditions. We also show that polarimetric information retrieved from photon starved images can be used in 3D object recognition problems. To the best of our knowledge, this is the first report on 3D polarimetric photon counting integral imaging

Validation of optical codes based on 3D nanostructures

Image information encoding using random phase masks produce speckle-like noise distributions when the sample is propagated in the Fresnel domain. As a result, information cannot be accessed by simple visual inspection. Phase masks can be easily implemented in practice by attaching cello-tape to the plain-text message. Conventional 2D-phase masks can be generalized to 3D by combining glass and diffusers resulting in a more complex, physical unclonable function. In this communication, we model the behavior of a 3D phase mask using a simple approach: light is propagated trough glass using the angular spectrum of plane waves whereas the diffusor is described as a random phase mask and a blurring effect on the amplitude of the propagated wave. Using different designs for the 3D phase mask and multiple samples, we demonstrate that classification is possible using the k-nearest neighbors and random forests machine learning algorithms

Compression of encrypted three-dimensional objects using digital holography

We present the results of applying data compression techniques to encrypted three-dimensional objects. The objects are captured using phase-shift digital holography and encrypted using a random phase mask in the Fresnel domain. Lossy quantization is combined with lossless coding techniques to quantify compression ratios. Lossless compression alone applied to the encrypted holographic data achieves compression ratios lower than 1.05. When combined with quantization and an integer encoding scheme, this rises to between 12 and 65 (depending on the hologram chosen and the method of measuring compression ratio), with good decryption and reconstruction quality. Our techniques are suitable for a range of secure three-dimensional object storage and transmission applications

Optical security and authentication using nanoscale and thin-film structures

Authentication of encoded information is a popular current trend in optical security. Recent research has proposed the production of secure unclonable ID tags and devices with the use of nanoscale encoding and thin-film deposition fabrication techniques, which are nearly impossible to counterfeit but can be verified using optics and photonics instruments. Present procedures in optical encryption provide secure access to the information, and these techniques are improving daily. Nevertheless, a rightful recipient with access to the decryption key may not be able to validate the authenticity of the message. In other words, there is no simple way to check whether the information has been counterfeited. Metallic nanoparticles may be used in the fabrication process because they provide distinctive polarimetric signatures that can be used for validation. The data is encoded in the optical domain, which can be verified using physical properties with speckle analysis or ellipsometry. Signals obtained from fake and genuine samples are complex and can be difficult to distinguish. For this reason, machine-learning classification algorithms are required in order to determine the authenticity of the encoded data and verify the security of unclonable nanoparticle encoded or thin-film-based ID tags. In this paper, we review recent research on optical validation of messages, ID tags, and codes using nanostructures, thin films, and 3D optical codes. We analyze several case scenarios where optically encoded devices have to be authenticated. Validation requires the combined use of a variety of multi-disciplinary approaches in optical and statistical techniques, and for this reason, the first five sections of this paper are organized as a tutorial

Fundamentals of 3D imaging and displays: a tutorial on integral imaging, light-field, and plenoptic systems

There has been great interest in researching and implementing effective technologies for the capture, processing, and display of 3D images. This broad interest is evidenced by widespread international research and activities on 3D technologies. There is a large number of journal and conference papers on 3D systems, as well as research and development efforts in government, industry, and academia on this topic for broad applications including entertainment, manufacturing, security and defense, and biomedical applications. Among these technologies, integral imaging is a promising approach for its ability to work with polychromatic scenes and under incoherent or ambient light for scenarios from macroscales to microscales. Integral imaging systems and their variations, also known as plenoptics or light-field systems, are applicable in many fields, and they have been reported in many applications, such as entertainment (TV, video, movies), industrial inspection, security and defense, and biomedical imaging and displays. This tutorial is addressed to the students and researchers in different disciplines who are interested to learn about integral imaging and light-field systems and who may or may not have a strong background in optics. Our aim is to provide the readers with a tutorial that teaches fundamental principles as well as more advanced concepts to understand, analyze, and implement integral imaging and light-field-type capture and display systems. The tutorial is organized to begin with reviewing the fundamentals of imaging, and then it progresses to more advanced topics in 3D imaging and displays. More specifically, this tutorial begins by covering the fundamentals of geometrical optics and wave optics tools for understanding and analyzing optical imaging systems. Then, we proceed to use these tools to describe integral imaging, light-field, or plenoptics systems, the methods for implementing the 3D capture procedures and monitors, their properties, resolution, field of view, performance, and metrics to assess them. We have illustrated with simple laboratory setups and experiments the principles of integral imaging capture and display systems. Also, we have discussed 3D biomedical applications, such as integral microscopy

Roadmap on optical security

Postprint (author's final draft

Three Dimensional Visualization of Long Range Scenes by Photon Counting Mid-Wave Infrared Integral Imaging

Integral Imaging under photon counting conditions has found different three-dimensional (3D) imaging applications, including 3D image reconstruction and recognition. In this letter, we present the application of the maximum likelihood (ML) estimation method for visualization of 3D scenes in photon starved environments using Mid-Wave Infrared 3D data of real scenes acquired at distances ranging from 50m to more than 2km. To the best of our knowledge, this is the first report on Mid-Wave Infrared 3D photon counting integral imaging of distant scenes

Integral imaging acquisition and processing for visualization of photon counting images in the mid-wave infrared range

Penència presentada al SPIE Conference Volume 9867 "Three-Dimensional Imaging, Visualization, and Display 2016" organitzat per Bahram Javidi i Jung-Young Son i celebrat a Baltimore, (Maryland, United States) el 17 d' abril de 2016In this paper, we present an overview of our previously published work on the application of the maximum likelihood (ML) reconstruction method to integral images acquired with a mid-wave infrared detector on two different types of scenes: one of them consisting of a road, a group of trees and a vehicle just behind one of the trees (being the car at a distance of more than 200m from the camera), and another one consisting of a view of the Wright Air Force Base airfield, with several hangars and different other types of installations (including warehouses) at distances ranging from 600m to more than 2km. Dark current noise is considered taking into account the particular features this type of sensors have. Results show that this methodology allows to improve visualization in the photon counting domain