### Abstract

FT-IR imaging employing a focal plane array (FPA) detector is often plagued by low signal-to-noise ratio (SNR) data. A mathematical transform that re-orders spectral data points into decreasing order of SNR is employed to reduce noise by retransforming the ordered data set using only a few relevant data points. This approach is shown to result in significant gains in terms of image fidelity by examining microscopically phase-separated composites termed polymer dispersed liquid crystals (PDLCs). The actual gains depend on the SNR characteristics of the original data. Noise is reduced by a factor greater than 5 if the noise in the initial data is sufficiently low. For a moderate absorbance level of 0.5 a.u., the achievable SNR by reducing noise is greater than 100 for a collection time of less than 4 min. The criteria for optimal application of a noise-reducing procedure employing the minimum noise fraction (MNF) transform are discussed and various variables in the process quantified. This noise reduction is shown to provide high-quality images for accurate morphological analysis. The coupling of mathematical transformation techniques with spectroscopic Fourier transform infrared (FT-IR) imaging is shown to result in high-fidelity images without increasing collection time or drastically modifying hardware.

Original language | English (US) |
---|---|

Pages (from-to) | 486-495 |

Number of pages | 10 |

Journal | Applied Spectroscopy |

Volume | 54 |

Issue number | 4 |

DOIs | |

State | Published - Apr 2000 |

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### ASJC Scopus subject areas

- Instrumentation
- Spectroscopy

### Cite this

*Applied Spectroscopy*,

*54*(4), 486-495. https://doi.org/10.1366/0003702001949898

**Route to higher fidelity FT-IR imaging.** / Bhargava, Rohit; Wang, Shi Qing; Koenig, Jack L.

Research output: Contribution to journal › Article

*Applied Spectroscopy*, vol. 54, no. 4, pp. 486-495. https://doi.org/10.1366/0003702001949898

}

TY - JOUR

T1 - Route to higher fidelity FT-IR imaging

AU - Bhargava, Rohit

AU - Wang, Shi Qing

AU - Koenig, Jack L.

PY - 2000/4

Y1 - 2000/4

N2 - FT-IR imaging employing a focal plane array (FPA) detector is often plagued by low signal-to-noise ratio (SNR) data. A mathematical transform that re-orders spectral data points into decreasing order of SNR is employed to reduce noise by retransforming the ordered data set using only a few relevant data points. This approach is shown to result in significant gains in terms of image fidelity by examining microscopically phase-separated composites termed polymer dispersed liquid crystals (PDLCs). The actual gains depend on the SNR characteristics of the original data. Noise is reduced by a factor greater than 5 if the noise in the initial data is sufficiently low. For a moderate absorbance level of 0.5 a.u., the achievable SNR by reducing noise is greater than 100 for a collection time of less than 4 min. The criteria for optimal application of a noise-reducing procedure employing the minimum noise fraction (MNF) transform are discussed and various variables in the process quantified. This noise reduction is shown to provide high-quality images for accurate morphological analysis. The coupling of mathematical transformation techniques with spectroscopic Fourier transform infrared (FT-IR) imaging is shown to result in high-fidelity images without increasing collection time or drastically modifying hardware.

AB - FT-IR imaging employing a focal plane array (FPA) detector is often plagued by low signal-to-noise ratio (SNR) data. A mathematical transform that re-orders spectral data points into decreasing order of SNR is employed to reduce noise by retransforming the ordered data set using only a few relevant data points. This approach is shown to result in significant gains in terms of image fidelity by examining microscopically phase-separated composites termed polymer dispersed liquid crystals (PDLCs). The actual gains depend on the SNR characteristics of the original data. Noise is reduced by a factor greater than 5 if the noise in the initial data is sufficiently low. For a moderate absorbance level of 0.5 a.u., the achievable SNR by reducing noise is greater than 100 for a collection time of less than 4 min. The criteria for optimal application of a noise-reducing procedure employing the minimum noise fraction (MNF) transform are discussed and various variables in the process quantified. This noise reduction is shown to provide high-quality images for accurate morphological analysis. The coupling of mathematical transformation techniques with spectroscopic Fourier transform infrared (FT-IR) imaging is shown to result in high-fidelity images without increasing collection time or drastically modifying hardware.

UR - http://www.scopus.com/inward/record.url?scp=0033752597&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033752597&partnerID=8YFLogxK

U2 - 10.1366/0003702001949898

DO - 10.1366/0003702001949898

M3 - Article

AN - SCOPUS:0033752597

VL - 54

SP - 486

EP - 495

JO - Applied Spectroscopy

JF - Applied Spectroscopy

SN - 0003-7028

IS - 4

ER -