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When electromagnetic radiation passes through a material, atoms or molecules transition from a lower to a higher energy state by absorbing radiation corresponding to the energy difference between the two states. The absorption of infrared (IR) radiation causes transitions between vibrational energy levels in a molecule. Therefore, IR spectroscopy is a useful analytical tool for determining the molecular structure of molecules.
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IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
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IR Frequency Region: X–H Stretching01:24

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In IR spectroscopy, signals produced by the X−H bonds (such as C−H, O−H, or N−H) can be observed in the frequency range of  2700–4000 cm–1. The C−H stretching vibration forms sharp bands in the region 2850–3000 cm–1. The presence of the O−H stretching vibration leads to the forming of an absorption band in the frequency range 3650–3200 cm−1. At the same time, N−H stretching can be confirmed by absorption bands in...
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When infrared (IR) radiation passes through a molecule, the bonds stretch or bend by absorbing the radiation. This absorption creates the molecule's absorption spectrum, which is the plot of its percentage transmittance versus wavenumber.
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Flame photometry, also known as flame emission spectrometry, is a technique used for the qualitative and quantitative analysis of elements present in a sample using a flame as the source of excitation energy. The concept of flame photometry was realized in the early 1860s by Kirchhoff and Bunsen, who discovered that specific elements emit characteristic radiation when excited in flames. The first instrument developed for this purpose was used to measure sodium (Na) in plant ash using a Bunsen...
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Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
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Infrared and Visual Image Fusion Based on a Local-Extrema-Driven Image Filter.

Wenhao Xiang1, Jianjun Shen1, Li Zhang1

  • 1Department of Electronic Engineering, Tsinghua University, Beijing 100084, China.

Sensors (Basel, Switzerland)
|April 13, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel local-extrema-driven image filter for infrared and visual image fusion. The method effectively combines features, outperforming eleven state-of-the-art techniques on the TNO dataset.

Keywords:
base imagebright feature mapdark feature mapinfrared and visual image fusionlocal-extrema-driven image filter

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Area of Science:

  • Computer Vision
  • Image Processing
  • Signal Processing

Background:

  • Infrared and visual image fusion aims to integrate complementary information from both modalities.
  • Existing methods often struggle to effectively preserve salient features from both image types.

Purpose of the Study:

  • To develop a novel image fusion method that effectively amalgamates infrared and visual image features.
  • To enhance the informative content of the fused image by leveraging local extrema for feature extraction.

Main Methods:

  • A novel local-extrema-driven image filter is proposed for image smoothing and feature extraction.
  • The filter is iteratively applied to extract multi-scale bright and dark feature maps.
  • Fusion of feature maps uses elementwise-maximum and elementwise-minimum strategies, while base images are fused using structural similarity and intensity.
  • The final fused image is constructed by combining fused feature maps and base images.

Main Results:

  • The proposed method demonstrates superior performance in infrared and visual image fusion.
  • Experimental results on the TNO dataset show the method matches or surpasses eleven state-of-the-art fusion techniques.
  • Both qualitative and quantitative assessments confirm the effectiveness of the proposed approach.

Conclusions:

  • The local-extrema-driven filter provides an effective mechanism for infrared and visual image fusion.
  • The developed fusion strategy successfully integrates complementary features, leading to enhanced image quality.
  • The method offers a robust and high-performing solution for multi-modal image fusion applications.