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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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Improving single pixel imaging performance in high noise condition by under-sampling.

Fangyuan Sha1, Sujit Kumar Sahoo1,2, Huy Quoc Lam3

  • 1Centre for Optoelectronics and Biophotonics (COEB), School of Electrical and Electronic Engineering, The Photonics Institute (TPI), Nanyang Technological University Singapore, 50 Nanyang Avenue, Singapore, 639798, Singapore.

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Summary
This summary is machine-generated.

Single-pixel imaging (SPI) offers a cost-effective alternative for various applications. This study compares Hadamard and Discrete Cosine Transforms, finding DCT superior for image quality with fewer measurements.

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Area of Science:

  • Optics and Photonics
  • Computational Imaging
  • Signal Processing

Background:

  • Single-pixel imaging (SPI) is a cost-effective alternative to traditional imaging systems, especially when detector arrays are expensive or unavailable.
  • Image reconstruction quality in SPI is influenced by sampling strategies, noise, and the type of transform used.
  • Understanding these factors is crucial for optimizing SPI performance.

Purpose of the Study:

  • To compare the performance of SPI using Hadamard Transform (HT) and Discrete Cosine Transform (DCT) under noisy conditions.
  • To investigate the impact of sampling strategies and measurement counts on reconstructed image quality.
  • To develop and validate a quality control technique for SPI.

Main Methods:

  • Comparative analysis of SPI performance with HT and DCT.
  • Evaluation of image reconstruction quality based on sampling order, ratio, noise, and transform type.
  • Demonstration using a large dataset of images and laboratory experiments.
  • Development and experimental validation of a SPI quality control technique.

Main Results:

  • Discrete Cosine Transform (DCT) yields higher image quality with fewer measurements compared to Hadamard Transform (HT).
  • An optimal number of measurements exists for balancing image information and noise, maximizing reconstruction quality.
  • The proposed SPI sampling strategy and quality control technique were validated through experiments.

Conclusions:

  • SPI offers a viable imaging solution, with DCT demonstrating superior performance over HT in terms of image quality and measurement efficiency.
  • Optimized sampling strategies and quality control are essential for maximizing SPI speed and image fidelity.
  • This research provides a practical framework for advancing SPI technology.