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相关概念视频

Deconvolution01:20

Deconvolution

541
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.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
541
Downsampling01:20

Downsampling

598
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...
598
Upsampling01:22

Upsampling

575
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...
575
Aliasing01:18

Aliasing

562
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...
562
Uniform Depth Channel Flow01:27

Uniform Depth Channel Flow

525
Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
525
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

686
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...
686

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相关实验视频

Updated: Jan 14, 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

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有效的多级梯度域过,用于图像和视频处理,具有增强的时间一致性.

Neelam Kumari1, Isha Kansal1, Preeti Sharma2

  • 1Chitkara University Institute of Engineering and Technology, Chitkara University.

Journal of visualized experiments : JoVE
|October 20, 2025
PubMed
概括

本研究介绍了一种高效的多尺度梯度域过器,用于图像和视频 dehazing. 该方法提高了清晰度,减少了文物,改善了实时应用的视觉质量.

科学领域:

  • 计算机视觉 计算机视觉
  • 图像处理 图像处理

背景情况:

  • 大气散射会降低图像清晰度,对计算机视觉任务构成挑战.
  • 现有的排气方法往往具有高的计算成本,并且可能会丢失重要的梯度细节.
  • 视频dehazing特别受到闪的文物的影响,限制了现实世界的应用.

研究的目的:

  • 为图像和视频提出一种高效,高质量的除尘技术.
  • 解决现有方法的局限性,包括计算成本,细节丢失和闪的文物.
  • 为了增强纹理和边缘保留,同时保持视频dehazing中的时间连贯性.

主要方法:

  • 建议使用多尺度梯度域加权引导图像过器 (GWGIF) 进行精细的传输地图估计.
  • 最少保存子样本 (MPS) 用于高效的大气参数估计和复杂性降低.
  • 引入了梯度相关系因子 (GCF),以减轻视频除尘中的闪文物.

主要成果:

  • 拟议的方法实现了卓越的感知质量,PIQE,NIQE和BRISQE分数分别为26.98,2.78和20.18.
  • 在视频解中,高时间连贯性被证明具有0.003.3的平均平方误差 (MSE) 偏差.
  • 与现有方法相比,在视频脱雾中观察到闪的文物显著减少.

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相关实验视频

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结论:

  • 拟议的基于GWGIF的除尘技术为图像和视频处理提供了更高的效率和视觉质量.
  • 该方法有效地保留了渐变细节,并改善了纹理/边缘保留.
  • 由于其性能和时间稳定性,其适合于实时应用,如自动驾驶和监控等.