Compressive Sensing via Low-Rank Gaussian Mixture Models

  • Huang G.
  • Jiang H.
  • Wilford P.
  • Yuan X.

We develop a new compressive sensing (CS) inversion algorithm by utilizing the Gaussian mixture model (GMM). While the compressive sensing is performed globally on the entire image as implemented in our lensless camera, a low-rank GMM is imposed on the local image patches. This low-rank GMM is derived via eigenvalue thresholding of the GMM trained on the projection of the measurement data, thus learned in situ. Extensive results on both simulation data and real data captured by the lensless camera verify the efficacy of the proposed algorithm. Our GMM model degrades to the piecewise linear estimator (PLE) if each patch is represented by a single Gaussian model. Following this, a low-rank PLE algorithm for CS inversion is also developed, which constructs an additional contribution of this paper. Since good results have been obtained via different algorithms when the measurement number is larger (more than 0.1 of the pixel numbers in the image), we hereby spend more efforts on the challenge case with a small number of measurements. Furthermore, we compare the CS reconstruction results using our algorithm with the JPEG compression. Simulation results demonstrate when limited bandwidth is available (a small number of measurements), our algorithm can achieve comparable results as the JPEG.

Recent Publications

August 09, 2017

A Cloud Native Approach to 5G Network Slicing

  • Francini A.
  • Miller R.
  • Sharma S.

5G networks will have to support a set of very diverse and often extreme requirements. Network slicing offers an effective way to unlock the full potential of 5G networks and meet those requirements on a shared network infrastructure. This paper presents a cloud native approach to network slicing. The cloud ...

August 01, 2017

Modeling and simulation of RSOA with a dual-electrode configuration

  • De Valicourt G.
  • Liu Z.
  • Violas M.
  • Wang H.
  • Wu Q.

Based on the physical model of a bulk reflective semiconductor optical amplifier (RSOA) used as a modulator in radio over fiber (RoF) links, the distributions of carrier density, signal photon density, and amplified spontaneous emission photon density are demonstrated. One of limits in the use of RSOA is the lower ...

July 12, 2017

PrivApprox: Privacy-Preserving Stream Analytics

  • Chen R.
  • Christof Fetzer
  • Le D.
  • Martin Beck
  • Pramod Bhatotia
  • Thorsten Strufe

How to preserve users' privacy while supporting high-utility analytics for low-latency stream processing? To answer this question: we describe the design, implementation and evaluation of PRIVAPPROX, a data analytics system for privacy-preserving stream processing. PRIVAPPROX provides three properties: (i) Privacy: zero-knowledge privacy (ezk) guarantees for users, a privacy bound tighter ...