40,940 research outputs found
No-reference image quality assessment through the von Mises distribution
An innovative way of calculating the von Mises distribution (VMD) of image
entropy is introduced in this paper. The VMD's concentration parameter and some
fitness parameter that will be later defined, have been analyzed in the
experimental part for determining their suitability as a image quality
assessment measure in some particular distortions such as Gaussian blur or
additive Gaussian noise. To achieve such measure, the local R\'{e}nyi entropy
is calculated in four equally spaced orientations and used to determine the
parameters of the von Mises distribution of the image entropy. Considering
contextual images, experimental results after applying this model show that the
best-in-focus noise-free images are associated with the highest values for the
von Mises distribution concentration parameter and the highest approximation of
image data to the von Mises distribution model. Our defined von Misses fitness
parameter experimentally appears also as a suitable no-reference image quality
assessment indicator for no-contextual images.Comment: 29 pages, 11 figure
Accelerated High-Resolution Photoacoustic Tomography via Compressed Sensing
Current 3D photoacoustic tomography (PAT) systems offer either high image
quality or high frame rates but are not able to deliver high spatial and
temporal resolution simultaneously, which limits their ability to image dynamic
processes in living tissue. A particular example is the planar Fabry-Perot (FP)
scanner, which yields high-resolution images but takes several minutes to
sequentially map the photoacoustic field on the sensor plane, point-by-point.
However, as the spatio-temporal complexity of many absorbing tissue structures
is rather low, the data recorded in such a conventional, regularly sampled
fashion is often highly redundant. We demonstrate that combining variational
image reconstruction methods using spatial sparsity constraints with the
development of novel PAT acquisition systems capable of sub-sampling the
acoustic wave field can dramatically increase the acquisition speed while
maintaining a good spatial resolution: First, we describe and model two general
spatial sub-sampling schemes. Then, we discuss how to implement them using the
FP scanner and demonstrate the potential of these novel compressed sensing PAT
devices through simulated data from a realistic numerical phantom and through
measured data from a dynamic experimental phantom as well as from in-vivo
experiments. Our results show that images with good spatial resolution and
contrast can be obtained from highly sub-sampled PAT data if variational image
reconstruction methods that describe the tissues structures with suitable
sparsity-constraints are used. In particular, we examine the use of total
variation regularization enhanced by Bregman iterations. These novel
reconstruction strategies offer new opportunities to dramatically increase the
acquisition speed of PAT scanners that employ point-by-point sequential
scanning as well as reducing the channel count of parallelized schemes that use
detector arrays.Comment: submitted to "Physics in Medicine and Biology
Revisiting spatial vision: toward a unifying model
We report contrast detection, contrast increment, contrast masking, orientation discrimination, and spatial frequency discrimination thresholds for spatially localized stimuli at 4° of eccentricity. Our stimulus geometry emphasizes interactions among overlapping visual filters and differs from that used in previous threshold measurements, which also admits interactions among distant filters. We quantitatively account for all measurements by simulating a small population of overlapping visual filters interacting through divisive inhibition. We depart from previous models of this kind in the parameters of divisive inhibition and in using a statistically efficient decision stage based on Fisher information. The success of this unified account suggests that, contrary to Bowne [Vision Res. 30, 449 (1990)], spatial vision thresholds reflect a single level of processing, perhaps as early as primary visual cortex
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Diagnostic Applications for Micro-Synchrophasor Measurements
This report articulates and justifies the preliminary selection of diagnostic applications for data from micro-synchrophasors (µPMUs) in electric power distribution systems that will be further studied and developed within the scope of the three-year ARPA-e award titled Micro-synchrophasors for Distribution Systems
Change blindness: eradication of gestalt strategies
Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task
Specific Effects of Spatial-frequency Uncertainty and Different Cue Types on Contrast Detection: Data and Models**Parts of this research were presented at the 17th ECVP (European Conference on Visual Perception) held 1994 at Eindhoven, The Netherlands.
AbstractIf the spatial-frequency of sinusoidal signals in a contrast-detection experiment varies randomly from trial to trial, then performance is decreased compared with that in a situation where it remains constant. This spatial-frequency uncertainty effect can more or less be compensated by presenting informative cues shortly before each trial. Single-band, as well as multiple-band models, have been proposed to explain the uncertainty and cuing effects. While the latter assume that under uncertainty multiple channels are monitored simultaneously, the former propose that in each trial a single, but sometimes inappropriate, channel is selected for monitoring. Until now it is open which of these models is valid. Therefore, psychometric functions were collected under different conditions of spatial-frequency uncertainty. It appears that the size of the uncertainty effect varies with spatial-frequency. This result can be explained by a multiple-band model, as computational analysis reveals. Copyright © 1996 Elsevier Science Ltd
Visual motion processing and human tracking behavior
The accurate visual tracking of a moving object is a human fundamental skill
that allows to reduce the relative slip and instability of the object's image
on the retina, thus granting a stable, high-quality vision. In order to
optimize tracking performance across time, a quick estimate of the object's
global motion properties needs to be fed to the oculomotor system and
dynamically updated. Concurrently, performance can be greatly improved in terms
of latency and accuracy by taking into account predictive cues, especially
under variable conditions of visibility and in presence of ambiguous retinal
information. Here, we review several recent studies focusing on the integration
of retinal and extra-retinal information for the control of human smooth
pursuit.By dynamically probing the tracking performance with well established
paradigms in the visual perception and oculomotor literature we provide the
basis to test theoretical hypotheses within the framework of dynamic
probabilistic inference. We will in particular present the applications of
these results in light of state-of-the-art computer vision algorithms
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