Sparse reconstruction of compressed sensing multispectral data using a cross-spectral multilayered conditional random field model

Edward Li; Mohammad Javad Shafiee; Farnoud Kazemzadeh; Alexander Wong

doi:10.1117/12.2188252

4 September 2015 Sparse reconstruction of compressed sensing multispectral data using a cross-spectral multilayered conditional random field model

Edward Li, Mohammad Javad Shafiee, Farnoud Kazemzadeh, Alexander Wong

Author Affiliations +

Proceedings Volume 9599, Applications of Digital Image Processing XXXVIII; 959902 (2015) https://doi.org/10.1117/12.2188252
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

Abstract

The broadband spectrum contains more information than what the human eye can detect. Spectral information from different wavelengths can provide unique information about the intrinsic properties of an object. Recently compressed sensing imaging systems with low acquisition time have been introduced. To utilize compressed sensing strategies, strong reconstruction algorithms that can reconstruct a signal from sparse observations are required. This work proposes a cross-spectral multi-layered conditional random field (CS-MCRF) approach for sparse reconstruction of multi-spectral compressive sensing data in multi-spectral stereoscopic vision imaging systems. The CS-MCRF will use information between neighboring spectral bands to better utilize available information for reconstruction. This method was evaluated using simulated compressed sensing multi-spectral imaging data. Results show improvement over existing techniques in preserving spectral fidelity while effectively inferring missing information from sparsely available observations.

Citation Download Citation

Edward Li, Mohammad Javad Shafiee, Farnoud Kazemzadeh, and Alexander Wong "Sparse reconstruction of compressed sensing multispectral data using a cross-spectral multilayered conditional random field model", Proc. SPIE 9599, Applications of Digital Image Processing XXXVIII, 959902 (4 September 2015); https://doi.org/10.1117/12.2188252

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