In this paper we study the noise stability of iterative algorithms developed in 1,2] for attenuat... more In this paper we study the noise stability of iterative algorithms developed in 1,2] for attenuation correction in Fluorescence Confocal Microscopy using FFT methods. In each iteration the convolution of the previous estimate is computed. It turns out that the estimators are robust to noise perturbation.
A new method of pattern-based analysis increases speed and accuracy and is invariant to image ori... more A new method of pattern-based analysis increases speed and accuracy and is invariant to image orientation.
A new method of pattern-based analysis increases speed and accuracy and is invariant to image ori... more A new method of pattern-based analysis increases speed and accuracy and is invariant to image orientation.
Visual information is difficult to search and interpret when the density of the displayed informa... more Visual information is difficult to search and interpret when the density of the displayed information is high or the layout is chaotic. Visual information that exhibits such properties is generally referred to as being "cluttered." Clutter should be avoided in information visualizations and interface design in general because it can severely degrade task performance. Although previous studies have identified computable correlates of clutter (such as local feature variance and edge density), understanding of why humans perceive some scenes as being more cluttered than others remains limited. Here, we explore an account of clutter that is inspired by findings from visual perception studies. Specifically, we test the hypothesis that the so-called "crowding" phenomenon is an important constituent of clutter. We constructed an algorithm to predict visual clutter in arbitrary images by estimating the perceptual impairment due to crowding. After verifying that this model can reproduce crowding data we tested whether it can also predict clutter. We found that its predictions correlate well with both subjective clutter assessments and search performance in cluttered scenes. These results suggest that crowding and clutter may indeed be closely related concepts and suggest avenues for further research.
In this paper we introduce and investigate similarity measures for convex polyhedra based on Mink... more In this paper we introduce and investigate similarity measures for convex polyhedra based on Minkowski addition and inequalities for the mixed volume and volume related to the Brunn–Minkowski theory. All measures considered are invariant under translations; furthermore, some of them are also invariant under subgroups of the affine transformation group. For the case of rotation and scale invariance, we prove
An object in the peripheral visual field is more difficult to recognize when surrounded by other ... more An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called ''crowding''. Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results from spatial feature integration necessary for object recognition. However, in the absence of convincing models, this theory has remained controversial. Here, we present a quantitative and physiologically plausible model for spatial integration of orientation signals, based on the principles of population coding. Using simulations, we demonstrate that this model coherently accounts for fundamental properties of crowding, including critical spacing, ''compulsory averaging'', and a foveal-peripheral anisotropy. Moreover, we show that the model predicts increased responses to correlated visual stimuli. Altogether, these results suggest that crowding has little immediate bearing on object recognition but is a by-product of a general, elementary integration mechanism in early vision aimed at improving signal quality. Citation: van den Berg R, Roerdink JBTM, Cornelissen FW (2010) A Neurophysiologically Plausible Population Code Model for Feature Integration Explains Visual Crowding. PLoS Comput Biol 6(1): e1000646.
In this paper we study the noise stability of iterative algorithms developed in 1,2] for attenuat... more In this paper we study the noise stability of iterative algorithms developed in 1,2] for attenuation correction in Fluorescence Confocal Microscopy using FFT methods. In each iteration the convolution of the previous estimate is computed. It turns out that the estimators are robust to noise perturbation.
A new method of pattern-based analysis increases speed and accuracy and is invariant to image ori... more A new method of pattern-based analysis increases speed and accuracy and is invariant to image orientation.
A new method of pattern-based analysis increases speed and accuracy and is invariant to image ori... more A new method of pattern-based analysis increases speed and accuracy and is invariant to image orientation.
Visual information is difficult to search and interpret when the density of the displayed informa... more Visual information is difficult to search and interpret when the density of the displayed information is high or the layout is chaotic. Visual information that exhibits such properties is generally referred to as being "cluttered." Clutter should be avoided in information visualizations and interface design in general because it can severely degrade task performance. Although previous studies have identified computable correlates of clutter (such as local feature variance and edge density), understanding of why humans perceive some scenes as being more cluttered than others remains limited. Here, we explore an account of clutter that is inspired by findings from visual perception studies. Specifically, we test the hypothesis that the so-called "crowding" phenomenon is an important constituent of clutter. We constructed an algorithm to predict visual clutter in arbitrary images by estimating the perceptual impairment due to crowding. After verifying that this model can reproduce crowding data we tested whether it can also predict clutter. We found that its predictions correlate well with both subjective clutter assessments and search performance in cluttered scenes. These results suggest that crowding and clutter may indeed be closely related concepts and suggest avenues for further research.
In this paper we introduce and investigate similarity measures for convex polyhedra based on Mink... more In this paper we introduce and investigate similarity measures for convex polyhedra based on Minkowski addition and inequalities for the mixed volume and volume related to the Brunn–Minkowski theory. All measures considered are invariant under translations; furthermore, some of them are also invariant under subgroups of the affine transformation group. For the case of rotation and scale invariance, we prove
An object in the peripheral visual field is more difficult to recognize when surrounded by other ... more An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called ''crowding''. Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results from spatial feature integration necessary for object recognition. However, in the absence of convincing models, this theory has remained controversial. Here, we present a quantitative and physiologically plausible model for spatial integration of orientation signals, based on the principles of population coding. Using simulations, we demonstrate that this model coherently accounts for fundamental properties of crowding, including critical spacing, ''compulsory averaging'', and a foveal-peripheral anisotropy. Moreover, we show that the model predicts increased responses to correlated visual stimuli. Altogether, these results suggest that crowding has little immediate bearing on object recognition but is a by-product of a general, elementary integration mechanism in early vision aimed at improving signal quality. Citation: van den Berg R, Roerdink JBTM, Cornelissen FW (2010) A Neurophysiologically Plausible Population Code Model for Feature Integration Explains Visual Crowding. PLoS Comput Biol 6(1): e1000646.
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Papers by J. Roerdink