Recovery of quantized compressed sensing measurements

Grigorios Tsagkatakis; Panagiotis Tsakalides

doi:10.1117/12.2083285

12 March 2015 Recovery of quantized compressed sensing measurements

Grigorios Tsagkatakis, Panagiotis Tsakalides

Proceedings Volume 9401, Computational Imaging XIII; 940106 (2015) https://doi.org/10.1117/12.2083285
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

Abstract

Compressed Sensing (CS) is a novel mathematical framework that has revolutionized modern signal and image acquisition architectures ranging from one-pixel cameras, to range imaging and medical ultrasound imaging. According to CS, a sparse signal, or a signal that can be sparsely represented in an appropriate collection of elementary examples, can be recovered from a small number of random linear measurements. However, real life systems may introduce non-linearities in the encoding in order to achieve a particular goal. Quantization of the acquired measurements is an example of such a non-linearity introduced in order to reduce storage and communications requirements. In this work, we consider the case of scalar quantization of CS measurements and propose a novel recovery mechanism that enforces the constraints associated with the quantization processes during recovery. The proposed recovery mechanism, termed Quantized Orthogonal Matching Pursuit (Q-OMP) is based on a modification of the OMP greedy sparsity seeking algorithm where the process of quantization is explicit considered during decoding. Simulation results on the recovery of images acquired by a CS approach reveal that the modified framework is able to achieve significantly higher reconstruction performance compared to its naive counterpart under a wide range of sampling rates and sensing parameters, at a minimum cost in computational complexity.

Citation Download Citation

Grigorios Tsagkatakis and Panagiotis Tsakalides "Recovery of quantized compressed sensing measurements", Proc. SPIE 9401, Computational Imaging XIII, 940106 (12 March 2015); https://doi.org/10.1117/12.2083285

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available