The Remarkable Visual Abilities of Nocturnal Insects: Neural Principles and Bioinspired Night-Vision Algorithms

Warrant, Eric J.; Oskarsson, Magnus; Malm, Henrik

doi:10.1109/jproc.2014.2332533

Cited by 24 publications

(17 citation statements)

References 78 publications

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“…Further work using intracellular recording could be used to determine the effect of kairomones on individual photoreceptors, as has been done to demonstrate higher night-time signal-to-noise ratios in photoreceptor cells of Limulus (Kaplan and Barlow, 1980). Increases in visual sensitivity often come at the cost of temporal resolution (Warrant, 1999(Warrant, , 2008Warrant et al, 2014). For example, higher sensitivity is associated with decreases in temporal resolution in mesopelagic and deep-sea crustaceans (Frank, 1999(Frank, , 2000Frank et al, 2012), and log K values are often negatively correlated with response latency in these animals (Frank, 2003).…”

Section: Discussionmentioning

confidence: 99%

“…Spatial summation is common in animals that need to resolve fast-moving objects as well as improve sensitivity (Warrant, 1999). Some crustaceans demonstrate spatial summation by increasing their visual acceptance angle (Bryceson and McIntyre, 1983;Hariyama et al, 2001) and other arthropod groups neurally pool information by laterally spreading and coupling the interneurons responsible for photoreceptor analysis (Greiner et al, 2004(Greiner et al, , 2005Warrant et al, 2014). Here, we used characteristics of eye structure to determine visual acceptance angle.…”

Section: Discussionmentioning

confidence: 99%

“…In a vertical migration scenario, for instance, this might place zooplankton at overall deeper depths in the water column throughout the diel cycle (Forward, 1985). Visual sensitivity may be controlled by structural and/or physiological mechanisms, as both play important roles mediating diel changes in visual sensitivity in crustaceans (Meyer-Rochow, 1999) and other arthropods (Battelle, 2002;Warrant et al, 2014). Here, electroretinogram (ERG) recordings and histological methods are employed to investigate kairomone-induced changes to retinal physiology and eye structure that could increase visual sensitivity and thereby result in kairomone-induced increases in photobehavior.…”

Section: Introductionmentioning

confidence: 99%

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Chemical cues from fish heighten visual sensitivity in larval crabs through changes in photoreceptor structure and function

Charpentier

Cohen

2015

Journal of Experimental Biology

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Several predator avoidance strategies in zooplankton rely on the use of light to control vertical position in the water column. Although light is the primary cue for such photobehavior, predator chemical cues or kairomones increase swimming responses to light. We currently lack a mechanistic understanding for how zooplankton integrate visual and chemical cues to mediate phenotypic plasticity in defensive photobehavior. In marine systems, kairomones are thought to be amino sugar degradation products of fish body mucus. Here, we demonstrate that increasing concentrations of fish kairomones heightened sensitivity of light-mediated swimming behavior for two larval crab species (Rhithropanopeus harrisii and Hemigrapsus sanguineus). Consistent with these behavioral results, we report increased visual sensitivity at the retinal level in larval crab eyes directly following acute (1-3 h) kairomone exposure, as evidenced electrophysiologically from V-log I curves and morphologically from wider, shorter rhabdoms. The observed increases in visual sensitivity do not correspond with a decline in temporal resolution, because latency in electrophysiological responses actually increased after kairomone exposure. Collectively, these data suggest that phenotypic plasticity in larval crab photobehavior is achieved, at least in part, through rapid changes in photoreceptor structure and function.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Chemical cues from fish heighten visual sensitivity in larval crabs through changes in photoreceptor structure and function

Charpentier

Cohen

2015

Journal of Experimental Biology

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“…The structure tensor has been used for image denoising in a number of previous work. We will closely follow the methods described in [14], [15], [16] and will here give the outline of their methods for completeness. One main difficulty of these methods is the parameter estimation and we will here show how our error modelling can be used to set parameters automatically.…”

Section: Application: Structure Adaptive Image Enhancementmentioning

confidence: 99%

Characterizing the structure tensor using gamma distributions

Oskarsson

2016

2016 23rd International Conference on Pattern Recognition (ICPR)

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Abstract-The structure tensor is a powerful tool describing the local intensity structure of an image or image sequence. In this paper we give a model for the noise distribution of the components of the tensor. In order to do so we have also investigated some properties of the gamma distribution. We show that, given an input image corrupted with Gaussian noise, the noise in the structure tensor can be modeled well by gamma distributions. We apply our model to automatic contrast enhancement of images taken under poor illumination. We show how our noise model can be used for automatic parameter selection in the filtering process, giving powerful results without the need for cumbersome parameter tuning.

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“…Depending on the application the role of the tone mapping operator (TMO) can be different, but in most applications the ability to capture both detail in darker areas and very bright ones is important. Tone mapping can also be an important component in image enhancement for, e.g., images taken under poor lighting [34,59].…”

Section: Introductionmentioning

confidence: 99%

Temporally Consistent Tone Mapping of Images and Video Using Optimal K-means Clustering

Oskarsson

2016

J Math Imaging Vis

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The field of high dynamic range imaging addresses the problem of capturing and displaying the large range of luminance levels found in the world, using devices with limited dynamic range. In this paper we present a novel tone mapping algorithm that is based on K-means clustering. Using dynamic programming we are able to not only solve the clustering problem efficiently, but also find the global optimum. Our algorithm runs in O(N 2 K ) for an image with N input luminance levels and K output levels. We show that our algorithm gives comparable results to state-of-theart tone mapping algorithms, but with the additional large benefit of a minimum of parameters. We show how to extend the method to handle video input. We test our algorithm on a number of standard high dynamic range images and video sequences and give qualitative and quantitative comparisons to a number of state-of-the-art tone mapping algorithms.

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The Remarkable Visual Abilities of Nocturnal Insects: Neural Principles and Bioinspired Night-Vision Algorithms

Cited by 24 publications

References 78 publications

Chemical cues from fish heighten visual sensitivity in larval crabs through changes in photoreceptor structure and function

Chemical cues from fish heighten visual sensitivity in larval crabs through changes in photoreceptor structure and function

Characterizing the structure tensor using gamma distributions

Temporally Consistent Tone Mapping of Images and Video Using Optimal K-means Clustering

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