Fluorescence modeling for optimized-binary compressive detection Raman spectroscopy

Abstract

The recently-developed optimized binary compressive detection (OB-CD) strategy has been shown to be capable of using Raman spectral signatures to rapidly classify and quantify liquid samples and to image solid samples. Here we demonstrate that OB-CD can also be used to quantitatively separate Raman and fluorescence features, and thus facilitate Raman-based chemical analyses in the presence of fluorescence background. More specifically, we describe a general strategy for fitting and suppressing fluorescence background using OB-CD filters trained on third-degree Bernstein polynomials. We present results that demonstrate the utility of this strategy by comparing classification and quantitation results obtained from liquids and powdered mixtures, both with and without fluorescence. Our results demonstrate high-speed Raman-based quantitation in the presence of moderate fluorescence. Moreover, we show that this OB-CD based method is effective in suppressing fluorescence of variable shape, as well as fluorescence that changes during the measurement process, as a result of photobleaching.

Precision of proportion estimation with binary compressed Raman spectrum

“…An alternative approach based on compressive detection has been proposed recently [4,[7][8][9][10] when the measured spectra is a linear combination of elementary spectrum of different species. In this methodology, proportion of known species can be estimated from few measurements (at least as many measurements as the number of species) .…”

“…In this article, we consider the problem of retrieving unknown proportions from a mixture of known species from compressed spectra that are obtained with measuring the intensity through optical binary filters. It is assumed that the mixed spectrum is a linear combination of elementary known spectra with unknown coefficients z i (see for example [4,[7][8][9][10][11] and references herein). The goal is thus to investigate precisely the performance of the compressed Raman method in comparison to full Raman techniques (i.e.…”

“…Indeed, a particular attention is provided to situations for which the number of filters is equal to the number of known species. It is demonstrated that, in that case, a simple linear mean square error estimation method [7][8][9][10] is efficient (i.e. has a variance equal to the Cramer-Rao Bound).…”

“…has a variance equal to the Cramer-Rao Bound). Estimation performance is also analyzed with Orthogonal Binary Filters (OBF) that constitute a subset of Binary Filters (BF) [7][8][9][10] and that are defined so that for each frequency at most one filter is equal to 1. Although practically difficult, the OBF method allows one to implement the filters in parallel when the measuring times for each binary filter are equal.…”

Compressive Detection of Highly Overlapped Spectra Using Walsh–Hadamard-Based Filter Functions

“…S2). Digital micromirror array device spectroscopy and imaging is often performed using only a single detector and the second mirror position is ignored., e.g., Wilcox et al, 3 Rehrauer et al, 8 Smith et al, 10 Fateley et al, 29 and Duarte et al; 30 a variant set of basis functions having values of þ1 and 0 called the S-matrix may then be used in Hadamard transform work. 21 However, the use of the Walsh functions with two detectors has distinct speed and S/N advantages.…”