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相关概念视频

Computed Tomography01:10

Computed Tomography

4.6K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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Upsampling01:22

Upsampling

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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...
265
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

249
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...
249
Deconvolution01:20

Deconvolution

197
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...
197
Convolution: Math, Graphics, and Discrete Signals01:24

Convolution: Math, Graphics, and Discrete Signals

298
In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
298
Downsampling01:20

Downsampling

192
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...
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相关实验视频

Updated: Jul 24, 2025

Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

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一种超混沌加密的强大的数字图像水印方法,具有大容量,使用混合域上的压缩传感.

Zhen Yang1,2, Qingwei Sun1, Yunliang Qi1

  • 1School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China.

Entropy (Basel, Switzerland)
|July 8, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了一个强大的半盲数字水印方案,增强图像版权保护和安全传输. 这种新的方法实现了对攻击的高容量和稳定性,优于现有技术.

关键词:
这就是为什么DWT DWT DWT这是SVDVD.压力感应感应 压力感应感应数字图像水印数字图像水印超混沌的地图隐藏的信息 隐藏的信息

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相关实验视频

Last Updated: Jul 24, 2025

Lensless Fluorescent Microscopy on a Chip
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Published on: August 17, 2011

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科学领域:

  • 计算机科学 计算机科学
  • 信息安全 信息安全
  • 数字图像处理 数字图像处理

背景情况:

  • 现有的数字水印技术往往难以同时平衡稳定性和容量.
  • 图像版权保护和安全传输仍然是数字多媒体的关键挑战.

研究的目的:

  • 提出一个强大的半盲图像水印方案,具有高容量和更高的安全性.
  • 解决当前方法在实现稳定性和高数据嵌入能力方面的局限性.

主要方法:

  • 离散波纹转换 (DWT) 用于载体图像分解.
  • 压缩采样用于水印图像压缩.
  • 一维和二维混乱地图 (TL-COTDCM) 的组合,用于安全编码.
  • 单值分解 (SVD) 用于嵌入水印.

主要成果:

  • 成功将8个256x256灰度水印图像嵌入到512x512载体图像中,实现比平均现有方法高出8倍的容量.
  • 通过标准化相关系数 (NCC) 和峰值信号与噪声比 (PSNR) 度量验证,对常见攻击具有很高的稳定性.
  • 与最先进的水印技术相比,在强度,安全性和容量方面取得了卓越的性能.

结论:

  • 拟议的数字水印系统在容量,稳定性和安全性方面提供了显著的改进.
  • 该方法显示了未来的多媒体应用程序的巨大潜力,这些应用程序需要安全的数据嵌入.
  • 整合DWT,压缩采样,混乱地图和SVD为数字水印提供了一个强大的方法.