Next Article in Journal
IEEE 802.11ah: A Technology to Face the IoT Challenge
Previous Article in Journal
Evaluation of Hyaluronic Acid Dilutions at Different Concentrations Using a Quartz Crystal Resonator (QCR) for the Potential Diagnosis of Arthritic Diseases
Previous Article in Special Issue
Noise Reduction Effect of Multiple-Sampling-Based Signal-Readout Circuits for Ultra-Low Noise CMOS Image Sensors
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(11), 1961; doi:10.3390/s16111961

Images from Bits: Non-Iterative Image Reconstruction for Quanta Image Sensors

1
School of Electrical and Computer Engineering, Purdue University, 465 Northwestern Ave, West Lafayette, IN 47907, USA
2
Department of Statistics, Purdue University, 250 N. University Street, West Lafayette, IN 47907, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Eric R. Fossum
Received: 8 September 2016 / Revised: 3 November 2016 / Accepted: 17 November 2016 / Published: 22 November 2016
(This article belongs to the Special Issue Photon-Counting Image Sensors)
View Full-Text   |   Download PDF [2815 KB, uploaded 22 November 2016]   |  

Abstract

A quanta image sensor (QIS) is a class of single-photon imaging devices that measure light intensity using oversampled binary observations. Because of the stochastic nature of the photon arrivals, data acquired by QIS is a massive stream of random binary bits. The goal of image reconstruction is to recover the underlying image from these bits. In this paper, we present a non-iterative image reconstruction algorithm for QIS. Unlike existing reconstruction methods that formulate the problem from an optimization perspective, the new algorithm directly recovers the images through a pair of nonlinear transformations and an off-the-shelf image denoising algorithm. By skipping the usual optimization procedure, we achieve orders of magnitude improvement in speed and even better image reconstruction quality. We validate the new algorithm on synthetic datasets, as well as real videos collected by one-bit single-photon avalanche diode (SPAD) cameras. View Full-Text
Keywords: single-photon image sensor; quanta image sensor (QIS); image reconstruction; quantized Poisson statistics; image denoising; Anscombe Transform; maximum likelihood estimation (MLE) single-photon image sensor; quanta image sensor (QIS); image reconstruction; quantized Poisson statistics; image denoising; Anscombe Transform; maximum likelihood estimation (MLE)
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Chan, S.H.; Elgendy, O.A.; Wang, X. Images from Bits: Non-Iterative Image Reconstruction for Quanta Image Sensors. Sensors 2016, 16, 1961.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top