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Related Experiment Video

Updated: May 8, 2026

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
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Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Pooling of first-order inputs in second-order vision.

Zachary M Westrick1, Michael S Landy

  • 1Department of Psychology, New York University, USA.

Vision Research
|September 3, 2013
PubMed
Summary

Human visual processing of texture relies on pooling across multiple spatial frequencies and orientations. This challenges the filter-rectify-filter model, suggesting broader initial filtering for accurate texture perception.

Keywords:
Second-order visionTexture

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Area of Science:

  • Visual perception
  • Computational neuroscience
  • Image processing

Background:

  • Texture pattern processing is often modeled by filter-rectify-filter (FRF) mechanisms.
  • The FRF model explains second-order pattern sensitivity using known first-order pattern processing.
  • Existing models predict lower sensitivity to high-frequency texture modulations than observed in humans.

Purpose of the Study:

  • To investigate the mechanisms underlying human texture perception.
  • To challenge the predictions of the standard filter-rectify-filter (FRF) model.
  • To provide psychophysical evidence for a revised model of texture processing.

Main Methods:

  • Utilized a cross-carrier adaptation experiment.
  • Measured modulation contrast sensitivity at low first-order contrast.
  • Employed psychophysical methods to assess human visual system responses.

Main Results:

  • The standard FRF model inaccurately predicts human sensitivity to high-frequency texture modulations.
  • Evidence suggests the human visual system pools across a wide range of spatial frequencies and orientations for texture demodulation.
  • Psychophysical data support the necessity of broad initial filtering for texture perception.

Conclusions:

  • The human visual system likely pools over first-order channels with diverse spatial frequencies and orientations for texture demodulation.
  • A revised model accounting for this pooling is necessary to explain observed texture perception.
  • Findings highlight the complexity of visual texture processing beyond simple filter-rectify-filter mechanisms.