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Related Concept Videos

Lossless Lines01:23

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In electrical engineering, a lossless transmission line is characterized by a purely imaginary propagation constant and a resistive characteristic impedance. The ABCD parameters, which describe the relationship between the input and output voltages and currents, indicate an equivalent π circuit with an imaginary series impedance and a shunt admittance. This results in a transmission line that, when the product of the phase constant (beta) and the length of the line is less than pi, exhibits...
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Consider a single-phase, two-wire, lossless transmission line terminated by an impedance at the receiving end and a source with Thevenin voltage and impedance at the sending end. The line, with length, has a surge impedance and wave velocity determined by the line's inductance and capacitance.
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The provided content explores the behavior of traveling waves on single-phase lossless transmission lines. It begins with a single-phase two-wire lossless transmission line of length Δx, characterized by a loop inductance LH/m and a line-to-line capacitance C F/m. These parameters result in a series inductance LΔx  and a shunt capacitance CΔx.
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Related Experiment Video

Updated: Feb 14, 2026

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
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Lossless Compression of Large Field-of-View Infrared Video Based on Transform Domain Hybrid Prediction.

Ya Liu1,2, Rui Zhang3, Yong Zhang1

  • 1Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China.

Sensors (Basel, Switzerland)
|February 13, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces an efficient lossless compression method for large field-of-view (FOV) infrared video, significantly improving computational efficiency by 19.3x while maintaining high compression performance.

Keywords:
discrete wavelet transformlarge field-of-view infrared videolossless compressionmulti-view high efficiency video coding (MV-HEVC)optimal direction prediction

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Area of Science:

  • Computer Vision
  • Image Processing
  • Video Compression

Background:

  • Large field-of-view (FOV) infrared imaging generates massive datasets, posing challenges for transmission and storage.
  • Existing compression techniques struggle with the high data volume from infrared video applications like target detection and remote sensing.

Purpose of the Study:

  • To develop an efficient lossless compression method for large FOV infrared video.
  • To address the challenges of data transmission and storage in infrared imaging.

Main Methods:

  • A hybrid prediction strategy in the transform domain using discrete wavelet transform (DWT) for frame decomposition.
  • Improved low-latency Multi-view High-Efficiency Video Coding (MV-HEVC) for low-frequency subbands, treating background frames as a reference view.
  • Pixel-wise clustered edge prediction and optimal direction prediction for high-frequency components to minimize residual energy.

Main Results:

  • The proposed method significantly outperforms mainstream video compression techniques.
  • Achieved compression performance comparable to MV-HEVC.
  • Demonstrated a 19.3-fold improvement in computational efficiency.

Conclusions:

  • The novel compression method offers a highly efficient solution for large FOV infrared video.
  • The hybrid prediction strategy effectively balances compression performance and computational speed.
  • This advancement is crucial for applications requiring real-time processing of large infrared datasets.