Abstract

Numerous findings indicate that spatial phase bears an important cognitive information. Distortion of phase affects topology of edge structures and makes images unrecognizable. In turn, appropriately phase-structured patterns give rise to various illusions of virtual image content and apparent motion. Despite a large body of phenomenological evidence not much is known yet about the role of phase information in neural mechanisms of visual perception and cognition. Here, we are concerned with analysis of the role of spatial phase in computational and biological vision, emergence of visual illusions and pattern recognition. We hypothesize that fundamental importance of phase information for invariant retrieval of structural image features and motion detection promoted development of phase-based mechanisms of neural image processing in course of evolution of biological vision. Using an extension of Fourier phase correlation technique, we show that the core functions of visual system such as motion detection and pattern recognition can be facilitated by the same basic mechanism. Our analysis suggests that emergence of visual illusions can be attributed to presence of coherently phase-shifted repetitive patterns as well as the effects of acuity compensation by saccadic eye movements. We speculate that biological vision relies on perceptual mechanisms effectively similar to phase correlation, and predict neural features of visual pattern (dis)similarity that can be used for experimental validation of our hypothesis of “cognition by phase correlation.”

Highlights

  • Continuous evolution of biological systems implicates a common origin of different functions and mechanisms that emerged as a result of successive modification of one advantageous basic principle

  • Since pioneering works of Hubel and Wiesel (1962, 1968), Campbell and Robson (1968), Blakemore and Campbell (1969), Blakemore et al (1969), and Thomas et al (1969) it is known that different groups of neurons in the visual cortex show selective response to spatial-temporal characteristics of visual stimuli and operate as spatially organized filters that extract particular image features within a certain range of their sensitivity

  • We review theoretical properties of phase using an extension of the Fourier phase correlation technique and demonstrate how phase information can be used for edge enhancement, motion detection, and pattern recognition

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Summary

Introduction

Continuous evolution of biological systems implicates a common origin of different functions and mechanisms that emerged as a result of successive modification of one advantageous basic principle. Since pioneering works of Hubel and Wiesel (1962, 1968), Campbell and Robson (1968), Blakemore and Campbell (1969), Blakemore et al (1969), and Thomas et al (1969) it is known that different groups of neurons in the visual cortex show selective response to spatial-temporal characteristics of visual stimuli and operate as spatially organized filters (receptive fields) that extract particular image features (i.e., spatial frequency, orientation) within a certain range (bandwidth) of their sensitivity. Divisive normalization of neuronal filter responses (Heeger, 1992; Schwartz and Simoncelli, 2001), These findings support the concept of neural transformation of retinal images into frequency domain characteristics (i.e., phase and amplitude) that, in turn, serve as an input for subsequent higher-order mechanisms and functions of visual perception and cognition. We make suggestions for experimental evaluation of our theoretical predictions

Invariants of Ecological Environment and Evolution of Vision
The Role of Phase from the Viewpoint of Computer Vision
Importance of Phase and Amplitude
Pattern Recognition using Phase Correlation
Discussion

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