Visual Pattern Analyzers
The visual system must extract from the light that falls on the retina meaningful information about what is where in our environment. At an early stage it analyzes the incoming sensory data along many dimensions of pattern vision, e.g. spatial frequency, orientation, velocity, eye-of-origin. Visual Pattern Analyzers provides a definitive account of current knowledge about this stage of visual processing. Nowhere else can such a comprehensive summarty of the lower level pattern analyzers be found. The book's emphasis is on psychophysical experiments measuring the detection and identification of near-threshold patterns -- and the mathematical models, such as multidimensional signal-detection theory, used to draw inferences from such experimental results -- but neurophysiological evidence is presented and compared critically to the psychophysical evidence. Introductory material on psychophysical methods, signal detection theory, and the mathematics of Fourier analysis is given in order to make the book more accessible to all who are interested in the lower or higher levels of visual perception. This volume will be of great value to researchers and graduate students in the fields of vision and perception. Within the scientific community there is wide interest in the visual system, and the book will be of use to investigators in many fields, including psychophysics, neuroscience, ophthalmology and optics, computer science, and cognitive and experimental psychology.
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adapting stimulus amplitude analyzer outputs analyzer's output analyzers sensitive assumed Assumption axis blank c/deg cells chapter component compound gratings compound stimulus contrast sensitivity decision rule decision variable different spatial discrimination discussed equally detectable example forced-choice Fourier transform fovea Gabor functions Gaussian function Graham high-threshold horizontal independent-analyzers models inhibition intensity intermixed condition interval Kulikowski linear lyzers maximum-output mean luminance mechanisms microanalyzers monitored multiple analyzers multiple-analyzers model Nachmias near-threshold neurons number of cycles observer orientation panel of Fig paradigm parameter peak plotted predictions probabilistically independent probability distribution probability summation psychometric function psychophysical quency Quick pooling formula receptive fields ROC curves selective sensitivity functions simple stimuli single analyzer sinusoidal gratings spatial extent spatial frequency spatial phase spatial position spatial-frequency bandwidth spatial-frequency dimension stim sum-of-outputs summation experiments temporal frequency temporal-frequency test stimulus tion Tolhurst trial uncertainty effects vectors vertical Vision Research visual visual system weighting functions width window function zero
Page 618 - Detection of noisy visual targets: Models for the effects of spatial uncertainty and signal-to-noise ratio.