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Related Concept Videos

Downsampling01:20

Downsampling

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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...
755
Computed Tomography01:10

Computed Tomography

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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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Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

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DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
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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...
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X-ray Imaging01:24

X-ray Imaging

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German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
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Histogram01:05

Histogram

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The histogram is a graphical representation in the x-y form of data distribution in a data set. The horizontal x-axis is labeled with what the data represents (for instance, distance from your home to school). The vertical y-axis is labeled either frequency or relative frequency (or percent frequency or probability).
A histogram graph consists of contiguous (adjoining) boxes. The heights of the bars correspond to frequency values. The graph will have the same shape with respective labels. The...
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Related Experiment Video

Updated: Mar 18, 2026

Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

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Context-Aware Image Compression.

Jacky C K Chan1, Ata Mahjoubfar1,2, Claire L Chen1,2

  • 1Department of Electrical Engineering, University of California Los Angeles, Los Angeles, California, United States of America.

Plos One
|July 2, 2016
PubMed
Summary
This summary is machine-generated.

We introduce a physics-based data compression method using photonic time stretch to dilate data, enabling lower downsampling rates. This novel approach improves compression efficiency without requiring phase recovery during decoding.

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Lensless Fluorescent Microscopy on a Chip
11:23

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Area of Science:

  • Physics
  • Signal Processing
  • Data Compression

Background:

  • Traditional data compression methods often face limitations in efficiently handling information-rich data segments.
  • Existing warped stretch compression techniques may require complex phase recovery for decoding.

Purpose of the Study:

  • To present a novel physics-based data compression method inspired by photonic time stretch.
  • To demonstrate improved data downsampling rates and compression efficiency.
  • To enable decoding without the need for phase recovery.

Main Methods:

  • Emulating group velocity dispersion to dilate information-rich data portions.
  • Implementing a coding operation for data dilation.
  • Performing rate-distortion analysis to evaluate compression performance.

Main Results:

  • Achieved data downsampling at a lower rate compared to methods without dilation.
  • Demonstrated improved Peak Signal-to-Noise Ratio (PSNR) compared to uniform downsampling.
  • Successfully implemented decoding without phase recovery.

Conclusions:

  • The photonic time stretch-inspired method offers an effective approach to data compression.
  • This technique enhances compression efficiency and simplifies the decoding process.
  • The method shows significant performance improvements over conventional uniform downsampling.