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Related Concept Videos

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
Downsampling01:20

Downsampling

When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
Upsampling01:22

Upsampling

Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next sampling...

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Related Experiment Video

Updated: Jun 16, 2026

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
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Published on: June 18, 2021

Total reduction of distorted echelle spectrograms: an automatic procedure.

R C Peterson, A M Title

    Applied Optics
    |February 16, 2010
    PubMed
    Summary

    A new semiautomatic procedure efficiently reduces high-dispersion echelle spectra using a microdensitometer and FORTRAN programs. This method aids in creating spectral atlases and determining line equivalent widths more rapidly.

    Area of Science:

    • Astronomy and Astrophysics
    • Spectroscopy
    • Data Reduction Techniques

    Background:

    • High-dispersion echelle spectra are crucial for detailed astronomical analysis.
    • Image tube detectors present unique challenges for spectral data reduction.
    • Accurate wavelength calibration and intensity measurements are essential.

    Purpose of the Study:

    • To develop and present a semiautomatic procedure for reducing echelle spectra.
    • To improve the efficiency and accuracy of spectral data processing.
    • To facilitate the creation of spectral atlases and measurement of line properties.

    Main Methods:

    • Utilizing a computer-controlled microdensitometer to trace curved spectral orders.
    • Employing a FORTRAN program to calculate spectral order curvature based on grating and distortion parameters.

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  • Scanning spectra with a narrow slit (0.012 A) for high resolution.

    • Main Results:

    • A typical echelle spectrum (25 orders, 1500 A) can be processed efficiently.
    • Generation of an intensity vs. wavelength atlas and determination of equivalent widths for approximately 300 lines are achievable within one day.
    • The procedure provides a detailed account of reduction steps and time requirements.

    Conclusions:

    • The described semiautomatic procedure offers an effective method for echelle spectra reduction.
    • This technique significantly enhances the speed of producing spectral data products.
    • The detailed discussion aids researchers in implementing and evaluating the reduction process.