My current research interests occupy the intersection of physical optics and signal processing, with an emphasis on the use of structured illumination. But, in previous years I have worked on a broad array of topics. A brief selection of past and present efforts are summarized in this page. I encourage you to navigate the tabs on this page for more information.
  • OMNISCIENT (status: ongoing)
    The acquisition and sensing mechanism in existing electro-optic imagers is optimized for line of sight operation. As a result, imagers cannot discern objects that are beyond the line of sight and potentially hidden from view. The OMNISCIENT program seeks to transform image sensing by exploiting the wave nature of light and the availability of scattering surfaces, in identifying a latent image of the unobservable objects.

  • Adaptive electro-optic (EO) sensing using active illumination (status: ongoing)
    This research effort aims to build imagers whose functionality may be rapidly adapted to suit evolving tactical needs. Among other things, these imagers are expected to support target/threat detection and identification at increased standoff, in a wide field of regard, with the highest clarity, through the cover of darkness and obscurants. The development of such imagers is facilitated by two recent innovations 
    • Emergence of computational imagers that afford novel imaging capabilities by manipulating the light distribution in the object and/or image volumes.  Examples of novel capabilities includes simultaneous super-resolved imaging and ranging.
    • Development of engineered optical beams that can squeeze light into regions smaller than the diffraction limit 

  • Pushing the limits of imaging using patterned illumination (status: complete)
    With the aid of DoD funding, my group at SMU has developed computational imagers whose resolving power is fully decoupled from the constraints imposed by the collection optics (such as diffraction and aberrations) and the detector (varying degrees of aliasing ranging from single photodiode to focal plane array). Additionally, these imagers feature support for point spread function engineering, foveated imaging and ranging. Such disparate capabilities are realized by processing images acquired under spatially patterned illumination. The Moiré fringes arising from the heterodyning of object detail and the illumination pattern, encapsulate spatial frequencies lost to diffraction. The deformations in the phase of the detected illumination pattern, encode range information.

    This work has been recognized with multiple awards. More information on the research effort is available here.

  • Multi-spectral Spatial Frequency Response estimation (status: complete)
    The Spatial Frequency Response (SFR) of a digital image acquisition system neatly encapsulates the influence of optical elements, pixel MTF and camera electronics, on image quality. The slanted-edge algorithm outlined in the ISO12233 standard is the gold standard for identifying the SFR. Critical examination of the slanted-edge method for multispectral cameras revealed inaccuracies in the estimated SFR, on account of demosaicing. The objective of this research effort was to resolve inaccuracies in the estimated SFR, by eliminating the need for demosaicing. The task is accomplished by accommodating the sparse sampling structure of the Bayer color filter array (CFA) within the slanted edge method. The method facilitates the comparison of the image quality of cameras with vastly differing CFA architectures, and help characterize the impact of a specific demosaicing algorithm on image quality.

    Additional information is available here.

  • Surpassing the detector resolution limit using Digital Super Resolution techniques (status: complete)
    The wealth of literature on the topic of Digital Super Resolution fail to provide satisfactory answers to simple questions such as
    • Is perfect recovery of an optically band-limited image possible under precise knowledge of translational motion ?
    • What are preferred optical PSF's (and focal plane masks) for digital super-resolution ?
    • Under what conditions can we disregard the use of regularization ?
    The present work sought to answer these questions by examining the connection between Digital Super Resolution, Papoulis's Generalized Sampling Theorem and maximally decimated perfect reconstruction filter-banks.

    Additional information is available here.

  • Metrology using commodity ToF (Time-of-Flight) sensors (status: ongoing)
    Accurate measurement of the physical distance to an object (ranging) has numerous applications in areas ranging from metrology to logistics. The commercial availability of photonic mixer devices has made it increasingly simple to acquire range information using a temporally modulated light source. The time difference between the incident and reflected light paths determines the distance to each scene point. The mechanics of ranging using the above notion is predicated on the availability of a single-bounce light path from the illumination source to individual sensor pixels. However, the view is inconsistent with the infinitely many ways in which light is transported from the source to the detector. The result is measurement errors in the estimated scene geometry.
        The problem has gained tremendous attention in the vision community and a variety of inreasingly sophisticated solutions have emerged.  Our exceedingly simple solution to the problem is inspired by point-scanning LiDAR. We seek to replace the flood-illumination module in commodity ToF sensors with a fan-out of spatially confined beams. A range map of the scene is assembled by consolidating range measurements that are acquired as the illumination pattern scans the scene.

  • Unbiased Least Squares Parameter estimation (status: complete)
    This research effort dispels popular notions concerning the use of Least Squares estimators (LSE) in computer vision (CV). It is widely believed that coordinate normalization is mandatory in LS parameter estimation, and that the heteroscedastic nature of LSE in CV induces a larger bias in LSE compared to maximum likelihood estimation (MLE). The first notion is dispelled by extending the notion of coordinate system invariance in LS curve fitting, to parameter estimation in computer vision. This reveals the existence of a family of LS estimators that are invariant to coordinate normalization and consequently do not need coordinate normalization. The second notion is dispelled by using higher-order perturbation analysis of linear systems, to demonstrate the existence of LS methods with a smaller bias compared to the ML estimator.

    Additional information is available in these publications: Paper1, Paper2, Paper3, Paper4, Paper5

  • Image Inpainting using Two-View Geometry (status: complete)
    This work examines the problem of removing occluders in an image using inpainting. We develop a geometric method that utilizes a second image of the scene from a different viewpoint, to inpaint the occluded objects. We recover the missing intensities by using the geometric relationship between corresponding points in the two images. The relationship is generally specified by the "epipolar line constraint", and degenerates to a projective homography under special circumstances. We fill-in missing pixels by copying information from the respective epipolar lines in the second image. The success of the approach hinges on the ability to estimate the "epipolar line constraint" from noisy correspondences. To this end, we analyze the uncertainty in estimating a homography from noisy correspondences. We rely on the knowledge of this uncertainty to identify parallax vectors best suited for estimating the epipolar geometry. We do not make any explicit assumptions about the nature or the extent of camera motion, only requiring that the occluded objects are static and undergo limited perspective change.

    Additional information is available here.
  • Low-cost instrument for cervical screening in resource constrained settings (status: ongoing)
    More information on this inter-disciplinary research effort will be made available soon.

  • Dynamic range compression for photography (status: complete)
    Traditional imaging sensors struggle to capture the wide dynamic range of natural scenes with exceedingly high contrast. The result is saturation and underexposure of the captured images. The aim of this research effort was to build a computational model for contrast perception that reduces the wide dynamic range in a scene, while still preserving the details. The idea is to preserve local contrast variations (reflectance) and attenuate the intensity (illumination) in areas of high-contrast. The success of the technique hinges on the ability to factorize the captured image into the illumination and reflectance components. An estimate of the illumination component is obtained by solving a modified heat equation that is initialized with the captured image field.

    Additional information is available here: Paper, Slide deck

  • Systematically reversing alpha-blended onscreen graphics using Adaptive Techniques (status: complete)
    This work explores the use of standard adaptive filtering techniques in suppressing broadcast logo's embedded in television material. The real time processing requirements of the problem necessitate the use of adaptive filters with low computational burden. The proposed approach uses a simplified version of the standard adaptive sinusoidal interference canceller, in an attempt to suppress the logo at the pixel level. An array of these pixel level logo suppressors is used to suppress the complete logo.

    Additional information is available here.

  • Identified as a DARPA Riser for the year 2015
    One of 54 early career researchers recognized as up-and-coming standouts in their fields, capable of discovering and leveraging innovative opportunities for technological surprise. The research effort recognized in this award is described here.

  •     Awards as graduate student
  • Placed 3rd in the 2011 edition of the Invent Your Future competition sponsored by Noetic Technologies

  • Placed 2nd in the 2011 edition of the World’s Best Technologies poster competition

  • Placed 2nd in the 2011 edition of the Cox Business Plan Competition hosted by SMU

  • Best Graduate Research for 2009 (SMU)

  • Best Teaching Assistant for 2007 (SMU)

  • Acknowledgment

    I would like to acknowledge the help of the following individuals in shaping my research efforts: Prof. Marc Christensen, Prof. Panos Papamichalis, Dr. Predrag Milojkovic, Prof.Kenichi Kanatani, Indranil Sinharoy, Dr.Vikrant Bhakta and Prof. Dinesh Rajan.