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IR Frequency Region: Fingerprint Region01:03

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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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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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Dual-Encoder UNet-Based Narrowband Uncooled Infrared Imaging Denoising Network.

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  • 1MOE Key Laboratory of Optoelectronic Imaging Technology and System, Beijing Institute of Technology, Beijing 100081, China.

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Summary
This summary is machine-generated.

This study introduces a novel dual-encoder network to denoise infrared images from hazardous gas leak detection. The method effectively removes mixed noise, significantly improving image quality for industrial safety applications.

Keywords:
dual-encoder UNetinfrared focal plane detectorthermal imaging denoisinguncooled infrared

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Area of Science:

  • Infrared Imaging Technology
  • Signal Processing
  • Artificial Intelligence

Background:

  • Uncooled infrared imaging is crucial for detecting hazardous gas leaks.
  • Narrowband filters in these systems capture low incident energy, causing mixed noise (fixed pattern and Gaussian).
  • Existing denoising methods are ineffective against this composite noise, hindering gas plume identification.

Purpose of the Study:

  • To develop an advanced denoising network for narrowband uncooled infrared images.
  • To effectively address the challenge of mixed noise in infrared gas leak detection.
  • To enhance the signal-to-noise ratio for clearer identification of gas plumes.

Main Methods:

  • A UNet-structured dual-encoder network was designed.
  • Two encoders, Basic Scale Residual Attention (BSRA) and Enlarged Scale Residual Attention (ESRA), were developed to capture noise at different scales.
  • Noise features from both scales were fused and processed by a decoder for image reconstruction.

Main Results:

  • The proposed network effectively denoises composite noise in narrowband uncooled infrared images.
  • Objective and subjective evaluations confirmed superior performance compared to existing methods.
  • Significant enhancement of the signal-to-noise ratio was achieved.

Conclusions:

  • The developed dual-encoder network offers a robust solution for denoising infrared images affected by mixed noise.
  • This technology holds significant potential for improving hazardous gas leak detection, remote sensing, and medical imaging.
  • The method enhances the practical applicability of uncooled infrared imaging systems in critical industrial and scientific fields.