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Related Concept Videos

Aliasing01:18

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original signal...
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...
Bandpass Sampling01:17

Bandpass Sampling

In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2. The spectrum...

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Related Experiment Video

Updated: Jun 13, 2026

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects
10:16

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects

Published on: February 8, 2014

Parameter extraction by holographic filtering.

J L Horner1, H J Caulfield

  • 1Rome Air Development Center, Deputy for Electronic Technology, Hanscom Air Force Base, Massachusetts 01731, USA.

Applied Optics
|April 15, 2010
PubMed
Summary
This summary is machine-generated.

This study demonstrates how holographic matched filter sensitivity to rotation can be leveraged for rapid, accurate angle estimation. Novel composite filters enable electronic searches, improving pattern recognition systems without mechanical components.

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Area of Science:

  • Optics and Photonics
  • Pattern Recognition
  • Image Processing

Background:

  • Holographic matched filter (HMF) based pattern recognition is sensitive to object rotation and scale.
  • This sensitivity has historically limited HMF applications, requiring complex compensation mechanisms.
  • Developing methods to utilize this inherent sensitivity is crucial for advancing HMF capabilities.

Purpose of the Study:

  • To demonstrate the use of HMF sensitivity for accurate parameter estimation.
  • To develop a method for rapid, signal-magnitude independent measurement of rotation angles.
  • To implement a composite filter approach for electronic search and parameter determination.

Main Methods:

  • Utilized three matched filters multiplexed onto a single hologram, positioned at -15, 0, and 15 degrees.
  • Performed signal-magnitude independent measurements of rotation angles within the range of -15 to +15 degrees.
  • Employed electronic searching in the output plane of the composite filter.

Main Results:

  • Achieved a worst-case accuracy of 1.0 degrees (95% confidence) for intermediate rotation angles.
  • Demonstrated rapid estimation of rotation parameters.
  • Validated the effectiveness of the composite filter for electronic pattern recognition.

Conclusions:

  • The inherent sensitivity of HMFs to rotation can be effectively exploited for precise angle estimation.
  • Composite holographic filters offer a robust solution for electronic, real-time parameter measurement.
  • This approach eliminates the need for moving parts, simplifying and enhancing pattern recognition systems.