Preattentive texture discrimination with early vision mechanisms

We present a model of human preattentive texture perception. This model consists of three stages: (1) convolution of the image with a bank of even-symmetric linear filters followed by half-wave rectification to give a set of responses modeling outputs of V1 simple cells, (2) inhibition, localized in space, within and among the neural-response profiles that results in the suppression of weak responses when there are strong responses at the same or nearby locations, and (3) texture-boundary detection by using wide odd-symmetric mechanisms. Our model can predict the salience of texture boundaries in any arbitrary gray-scale image. A computer implementation of this model has been tested on many of the classic stimuli from psychophysical literature. Quantitative predictions of the degree of discriminability of different texture pairs match well with experimental measurements of discriminability in human observers

Measuring the spatial frequency selectivity of second-order texture mechanisms

AbstractRecent investigations of texture and motion perception suggest two early filtering stages: an initial stage of selective linear filtering followed by rectification and a second stage of linear filtering. Here we demonstrate that there are differently scaled second-stage filters, and we measure their contrast modulation sensitivity as a function of spatial frequency. Our stimuli are Gabor modulations of a suprathreshold, bandlimited, isotropic carrier noise. The subjects' task is to discriminate between two possible orientations of the Gabor. Carrier noises are filtered into four octave-wide bands, centered at m = 2, 4, 8, and 16 c/deg. The Gabor test signals are w = 0.5, 1, 2, 4 and 8 c/deg. The threshold modulation of the test signal is measured for all 20 combinations of m and w. For each carrier frequency m, the Gabor test frequency w to which subjects are maximally sensitive appears to be approximately 3–4 octaves below m. The consistent m × w interaction suggests that each second-stage spatial filter may be differentially tuned to a particular first-stage spatial frequency. The most sensitive combination is a second-stage filter of 1 c/deg with first-stage inputs of 8–16 c/deg. We conclude that second-order texture perception appears to utilize multiple channels tuned to spatial frequency and orientation, with channels tuned to low modulation frequencies appearing to be best served by carrier frequencies 8 to 16 times higher than the modulations they are tuned to detect

Methods for multi-spectral image fusion: identifying stable and repeatable information across the visible and infrared spectra

Fusion of images captured from different viewpoints is a well-known challenge in computer vision with many established approaches and applications; however, if the observations are captured by sensors also separated by wavelength, this challenge is compounded significantly. This dissertation presents an investigation into the fusion of visible and thermal image information from two front-facing sensors mounted side-by-side. The primary focus of this work is the development of methods that enable us to map and overlay multi-spectral information; the goal is to establish a combined image in which each pixel contains both colour and thermal information. Pixel-level fusion of these distinct modalities is approached using computational stereo methods; the focus is on the viewpoint alignment and correspondence search/matching stages of processing. Frequency domain analysis is performed using a method called phase congruency. An extensive investigation of this method is carried out with two major objectives: to identify predictable relationships between the elements extracted from each modality, and to establish a stable representation of the common information captured by both sensors. Phase congruency is shown to be a stable edge detector and repeatable spatial similarity measure for multi-spectral information; this result forms the basis for the methods developed in the subsequent chapters of this work. The feasibility of automatic alignment with sparse feature-correspondence methods is investigated. It is found that conventional methods fail to match inter-spectrum correspondences, motivating the development of an edge orientation histogram (EOH) descriptor which incorporates elements of the phase congruency process. A cost function, which incorporates the outputs of the phase congruency process and the mutual information similarity measure, is developed for computational stereo correspondence matching. An evaluation of the proposed cost function shows it to be an effective similarity measure for multi-spectral information

La perception d'attributs visuels de premier et deuxième ordres

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

Modelling the human perception of shape-from-shading

Shading conveys information on 3-D shape and the process of recovering this information is called shape-from-shading (SFS). This thesis divides the process of human SFS into two functional sub-units (luminance disambiguation and shape computation) and studies them individually. Based on results of a series of psychophysical experiments it is proposed that the interaction between first- and second-order channels plays an important role in disambiguating luminance. Based on this idea, two versions of a biologically plausible model are developed to explain the human performances observed here and elsewhere. An algorithm sharing the same idea is also developed as a solution to the problem of intrinsic image decomposition in the field of image processing. With regard to the shape computation unit, a link between luminance variations and estimated surface norms is identified by testing participants on simple gratings with several different luminance profiles. This methodology is unconventional but can be justified in the light of past studies of human SFS. Finally a computational algorithm for SFS containing two distinct operating modes is proposed. This algorithm is broadly consistent with the known psychophysics on human SFS