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Related Concept Videos

Interference and Diffraction02:18

Interference and Diffraction

Interference is a characteristic phenomenon exhibited by waves. When two electromagnetic waves interact with their peaks and troughs coinciding, a resulting wave with enhanced amplitude is produced. This is known as constructive interference. In this case, the two waves interacting are in phase with each other.
Atomic Emission Spectroscopy: Interference01:30

Atomic Emission Spectroscopy: Interference

In atomic emission spectroscopy (AES), high-temperature atomizers excite a broad range of elements and molecules that generate complex emissions from sources such as oxides, hydroxides, and flame combustion products in the flame or plasma. Several strategies can be employed to minimize spectral interferences caused by overlapping emission lines or bands. These include increasing instrument resolution, choosing alternative emission lines, optimally placing the detector in low-background regions,...
Atomic Absorption Spectroscopy: Interference01:25

Atomic Absorption Spectroscopy: Interference

Interference leads to systematic error in atomic absorption (AA) measurements by enhancing or diminishing the analytical signal or the background. These interferences can be grouped into three main categories: spectral interference, chemical interference, and physical interference.
Spectral interference occurs when signals from other elements or molecules overlap with the analyte signal, falsely elevating or masking the analyte's absorbance. This interference can be corrected using Zeeman,...
Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
Interference and Superposition of Waves01:07

Interference and Superposition of Waves

When two waves of the same nature occur in the same region simultaneously, they result in interference. Interference of waves implies that the net effect of the waves is the sum of the individual waves' effects. However, it does not imply that the individual waves affect the propagation of other waves.
Interference occurs in mechanical waves, such as sound waves, waves on a string, and surface water waves. Mechanical waves correspond to the physical displacement of particles. Hence,...
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are slanted or...

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Related Experiment Video

Updated: Jun 6, 2026

Implementation of a Reference Interferometer for Nanodetection
16:11

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Published on: April 26, 2014

Fringe detection in noisy complex interferograms.

E Trouvé, M Caramma, H Maître

    Applied Optics
    |November 25, 2010
    PubMed
    Summary

    A novel algorithm accurately estimates local frequencies in phase interferometric data, even with noise. This method enhances fringe analysis and image restoration for applications like synthetic aperture radar.

    Area of Science:

    • Signal Processing
    • Image Analysis
    • Interferometry

    Background:

    • Phase interferometric data analysis is crucial for various imaging techniques.
    • Estimating local frequencies in such data is often challenging due to noise.
    • Existing methods may struggle with multiplicative noise perturbations.

    Purpose of the Study:

    • To develop a new algorithm for accurate two-dimensional local frequency estimation in phase interferometric data.
    • To demonstrate the robustness of a conventional multiple-signal classification (MUSIC) algorithm against noise.
    • To introduce a faster algorithm for interferogram processing and a confidence measure for frequency estimates.

    Main Methods:

    • Utilized a complex sine-wave model to analyze algorithm performance.

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    Implementation of a Reference Interferometer for Nanodetection
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  • Applied the multiple-signal classification (MUSIC) algorithm to interferometric data.
  • Developed a novel, faster algorithm specifically for interferogram processing.
  • Proposed a confidence measure for the estimated frequencies.
  • Evaluated numerical performance using synthetic fringes.

    • Main Results:

    • Demonstrated that the conventional MUSIC algorithm can handle multiplicative noise.
    • Developed a faster algorithm for interferogram processing.
    • Introduced a confidence measure for frequency estimation.
    • Showcased the ability to restore noisy phase data using estimated fringe width and orientation.
    • Presented results of a complex phase filter on real synthetic aperture radar interferograms.

    Conclusions:

    • The new algorithm provides accurate two-dimensional local frequency estimates for phase interferometric data.
    • Frequency estimation enables the restoration of noisy phase data by determining fringe local width and orientation.
    • The developed methods show promise for processing real-world interferograms, particularly from synthetic aperture radar images.