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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...
Reducing Line Loss01:18

Reducing Line Loss

In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss in...
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.
Block Diagram Reduction01:22

Block Diagram Reduction

The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
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...
Double Resonance Techniques: Overview01:12

Double Resonance Techniques: Overview

Double resonance techniques in Nuclear Magnetic Resonance (NMR) spectroscopy involve the simultaneous application of two different frequencies or radiofrequency pulses to manipulate and observe two distinct nuclear spins. One important application of double resonance is spin decoupling, which selectively suppresses coupling with one type of nucleus while observing the NMR signal from another nucleus, simplifying the spectrum and enhancing resolution.
Spin decoupling is usually achieved by...

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Related Experiment Video

Updated: May 15, 2026

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
08:42

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

Noise reduction based on partial-reference, dual-tree complex wavelet transform shrinkage.

Massimo Fierro1, Ho-Gun Ha, Yeong-Ho Ha

  • 1School of Electronics Engineering, Kyungpook National University, Daegu 702-701, Korea. massimo.fierro@gmail.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 15, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to reduce noise in enhanced images, particularly those from random spray sampling techniques. The approach uses directional analysis via dual-tree complex wavelet transform (DTWCT) to minimize noise without assuming its statistical properties.

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Area of Science:

  • Image Processing
  • Computer Vision

Background:

  • Image enhancement methods, especially those using random spray sampling, can introduce or amplify noise.
  • The statistical distribution of noise in such enhanced images is often unknown, making traditional noise reduction difficult.

Purpose of the Study:

  • To propose a novel noise reduction technique for enhanced images.
  • To address noise issues without making assumptions about its statistical properties.

Main Methods:

  • Utilizing the human visual system's sensitivity to brightness changes by focusing on the luma channel.
  • Employing the dual-tree complex wavelet transform (DTWCT) for directional analysis, distinguishing it from standard discrete wavelet transform.
  • Calculating a directional structure map from the non-enhanced image's DTWCT coefficients.
  • Shrinking enhanced image coefficients based on the directional map and merging them with non-enhanced image coefficients.

Main Results:

  • A noise-reduced version of the enhanced image is successfully computed using inverse transforms.
  • The method effectively reduces noise while preserving image structures.
  • Numerical analysis confirms the validity and effectiveness of the proposed approach.

Conclusions:

  • The proposed method offers an effective way to reduce noise in enhanced images, particularly those generated by spray-based techniques.
  • It provides a robust solution by avoiding assumptions on noise statistics and leveraging directional information.
  • This technique has potential applications in various image processing scenarios requiring high-fidelity results.