• Low-Complexity Iterative Reconstruction Algorithms in Compressed Sensing

      Vasić, Bane; Marcellin, Michael W.; Declercq, David; Danjean, Ludovic; University of Arizona (International Foundation for Telemetering, 2013-10)
      In this paper we focus on two low-complexity iterative reconstruction algorithms in compressed sensing. These algorithms, called the approximate message-passing algorithm and the interval-passing algorithm, are suitable to recover sparse signals from a small set of measurements. Depending on the type of measurement matrix (sparse or random) used to acquire the samples of the signal, one or the other reconstruction algorithm can be used. We present the reconstruction results of these two reconstruction algorithms in terms of proportion of correct reconstructions in the noise free case. We also report in this paper possible practical applications of compressed sensing where the choice of the measurement matrix and the reconstruction algorithm are often governed by the constraint of the considered application.
    • Machine Vision and Autonomous Integration Into an Unmanned Aircraft System

      Dianics, James; Fasel, Hermann F.; Marcellin, Michael W.; Van Horne, Chris; University of Arizona (International Foundation for Telemetering, 2013-10)
      The University of Arizona's Aerial Robotics Club (ARC) sponsors the development of an unmanned aerial vehicle (UAV) able to compete in the annual Association for Unmanned Vehicle Systems International (AUVSI) Seafarer Chapter Student Unmanned Aerial Systems competition. Modern programming frameworks are utilized to develop a robust distributed imagery and telemetry pipeline as a backend for a mission operator user interface. This paper discusses the design changes made for the 2013 AUVSI competition including integrating low-latency first-person view, updates to the distributed task backend, and incremental and asynchronous updates the operator's user interface for real-time data analysis.
    • Spread Spectrum Signal Detection from Compressive Measurements

      Marcellin, Michael W.; Goodman, Nathan A.; Bilgin, Ali; Lui, Feng; University of Arizona (International Foundation for Telemetering, 2013-10)
      Spread Spectrum (SS) techniques are methods used to deliberately spread the spectrum of transmitted signals in communication systems. The increased bandwidth makes detection of these signals challenging for non-cooperative receivers. In this paper, we investigate detection of Frequency Hopping Spread Spectrum (FHSS) signals from compressive measurements. The theoretical and simulated performances of the proposed methods are compared to those of the conventional methods.
    • Validation for Visually lossless Compression of Stereo Images

      Marcellin, Michael W.; Bilgin, Ali; Feng, Hsin-Chang; University of Arizona (International Foundation for Telemetering, 2013-10)
      This paper described the details of subjective validation for visually lossless compression of stereoscopic 3 dimensional (3D) images. The subjective testing method employed in this work is adapted from methods used previously for visually lossless compression of 2 dimensional (2D) images. Confidence intervals on the correct response rate obtained from the subjective validation of compressed stereo pairs provide reliable evidence to indicate that the compressed stereo pairs are visually lossless.