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Topographical Estimation of Visual Population Receptive Fields by fMRI
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A perceptually relevant approach to ringing region detection.

Hantao Liu1, Nick Klomp, Ingrid Heynderickx

  • 1Department of Mediamatics, Delft University of Technology, Delft, 2628 CD, The Netherlands. Hantao.Liu@tudelft.nl

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 29, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to automatically detect ringing artifacts in compressed images without needing a reference image. The approach is efficient and considers how the human visual system (HVS) perceives these visual impairments.

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Area of Science:

  • Image processing
  • Computer vision
  • Human visual perception

Background:

  • Ringing artifacts degrade image quality in compressed images.
  • Accurate detection of these artifacts is crucial for image quality assessment.
  • Existing no-reference methods often lack efficiency or perceptual relevance.

Purpose of the Study:

  • To develop an efficient, no-reference method for detecting image regions affected by ringing artifacts.
  • To incorporate the physical properties of ringing and human visual system (HVS) characteristics.
  • To enable real-time applications by maintaining low computational complexity.

Main Methods:

  • Utilizes a perceptually relevant edge detector to identify regions susceptible to ringing.
  • Employs a visual masking model to assess the visibility of detected ringing artifacts.
  • Combines artifact structure analysis with HVS properties for robust detection.

Main Results:

  • The proposed method reliably detects regions with ringing artifacts.
  • Achieves high computational efficiency suitable for real-time processing.
  • Outperforms existing alternatives in ringing region detection accuracy and speed.

Conclusions:

  • The novel approach effectively identifies ringing-impaired regions in compressed images.
  • The method is both reliable and computationally efficient, validated by psychovisual experiments.
  • Presents a promising solution for no-reference ringing artifact detection in image compression.