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A Perceptive Evaluation of Volume Rendering Techniques
"... The display of space filling data is still a challenge for the community of visualization. Direct Volume Rendering (DVR) is one of the most important techniques developed to achieve direct perception of such volumetric data. It is based on semi-transparent representations, where the data are accumul ..."
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The display of space filling data is still a challenge for the community of visualization. Direct Volume Rendering (DVR) is one of the most important techniques developed to achieve direct perception of such volumetric data. It is based on semi-transparent representations, where the data are accumulated in a depth-dependent order. However, it produces images that may be difficult to understand, and thus several techniques have been proposed so as to improve its effectiveness, using for instance lighting models or simpler representations (e.g. Maximum Intensity Projection). In this paper we present two perceptual studies that question how DVR meets its goals, in either static or dynamic context. We show that a static representation is highly ambiguous, even in simple cases, but this can be counterbalanced by use of dynamic cues, i.e. motion parallax, provided that the rendering parameters are correctly tuned.
Lightness, brightness and transparency: A quarter century of new ideas, captivating demonstrations and unrelenting controversy. Vision Res 51: 652–673
, 2011
"... a b s t r a c t The past quarter century has witnessed considerable advances in our understanding of Lightness (perceived reflectance), Brightness (perceived luminance) and perceived Transparency (LBT). This review poses eight major conceptual questions that have engaged researchers during this per ..."
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a b s t r a c t The past quarter century has witnessed considerable advances in our understanding of Lightness (perceived reflectance), Brightness (perceived luminance) and perceived Transparency (LBT). This review poses eight major conceptual questions that have engaged researchers during this period, and considers to what extent they have been answered. The questions concern 1. the relationship between lightness, brightness and perceived non-uniform illumination, 2. the brain site for lightness and brightness perception, 3 the effects of context on lightness and brightness, 4. the relationship between brightness and contrast for simple patch-background stimuli, 5. brightness ''filling-in", 6. lightness anchoring, 7. the conditions for perceptual transparency, and 8. the perceptual representation of transparency. The discussion of progress on major conceptual questions inevitably requires an evaluation of which approaches to LBT are likely and which are unlikely to bear fruit in the long term, and which issues remain unresolved. It is concluded that the most promising developments in LBT are (a) models of brightness coding based on multi-scale filtering combined with contrast normalization, (b) the idea that the visual system decomposes the image into ''layers" of reflectance, illumination and transparency, (c) that an understanding of image statistics is important to an understanding of lightness errors, (d) Whittle's log W metric for contrast-brightness, (e) the idea that ''filling-in" is mediated by low spatial frequencies rather than neural spreading, and (f) that there exist multiple cues for identifying non-uniform illumination and transparency. Unresolved issues include how relative lightness values are anchored to produce absolute lightness values, and the perceptual representation of transparency. Bridging the gap between multi-scale filtering and layer decomposition approaches to LBT is a major task for future research.
Combining achromatic and chromatic cues to transparency
- J. Vision
, 2006
"... We investigated how achromatic and chromatic cues interact to produce transparency. Observers were shown six-region stimulus displays similar to those used by Kasrai & Kingdom (2001) and made adjustments of the color and luminance attributes of one of the filter regions to achieve the best perce ..."
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We investigated how achromatic and chromatic cues interact to produce transparency. Observers were shown six-region stimulus displays similar to those used by Kasrai & Kingdom (2001) and made adjustments of the color and luminance attributes of one of the filter regions to achieve the best percept of transparency. The dependent measure of primary interest was setting reliability, the reciprocal of setting variance. We wished to determine whether the combination of chromatic and achromatic information leads to enhanced reliability of perceived transparency. In Experiment 1, we measured reliability for achromatic, L, superimposed luminance with color, L+C, and superimposed luminance with polarity-reversing color, L+iC. We found that observers ’ reliability was highest for the L+C condition consistent with effective cue combination. In a second experiment, we compared setting reliability for L, L+C, and a new chromatic-only condition C. In the L+C condition, observers were asked to make separate and iterative settings of luminance and color to achieve the best percept of transparency. We compared their settings in L with the luminance settings in L+C and their settings in C to their color settings in L+C. Color adjustments were more reliable when accompanied by luminance information, but not vice versa. In Experiment 3, we manipulated the transmittance of the achromatic and chromatic filters separately, and investigated how this influences the settings made for each attribute. No systematic influence of filter transmittance on the settings made for perceived transparency was found. 3
Lightness constancy through transparency: Internal consistency in layered surface representations
- Vision Research
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Natural Decompositions of Perceived Transparency: Reply to Albert (2008)
"... In M. Singh and B. L. Anderson (2002), the authors proposed a model based on ratios of Michelson contrasts to explain how human observers quantitatively scale the perceived opacity of transparent surfaces. In subsequent work (B. L. Anderson, M. Singh, & J. Meng, 2006), the authors found that th ..."
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In M. Singh and B. L. Anderson (2002), the authors proposed a model based on ratios of Michelson contrasts to explain how human observers quantitatively scale the perceived opacity of transparent surfaces. In subsequent work (B. L. Anderson, M. Singh, & J. Meng, 2006), the authors found that this model failed to generalize to other contexts and replaced it with a new, more general model based on ratios of perceived contrasts. M. K. Albert’s (2008) main experiment aimed to test the model the authors have previously rejected. The authors argue that M. K. Albert’s experimental method was flawed and that his experiments did not test either the authors ’ original model or the authors ’ subsequent model that replaced it. M. K. Albert failed to provide any account of the data that the authors ’ model predicts, and he did not provide any theory to explain his own data. The authors conclude that the discrepancy between M. K. Albert’s results and all models of transparency results from problems in the methods used in his experiments, not from the shortcomings of extant theory.
A simple model describes large individual differences in simultaneous colour contrast
"... We report experimental evidence for substantial individual differences in the susceptibility to simultaneous colour contrast. Inter-estingly, we found that not only the general amount of colour induction varies across observers, but also the general shape of the curves describing asymmetric matching ..."
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We report experimental evidence for substantial individual differences in the susceptibility to simultaneous colour contrast. Inter-estingly, we found that not only the general amount of colour induction varies across observers, but also the general shape of the curves describing asymmetric matching data. A simple model based on von Kries adaptation and crispening describes the data rather well when we regard its free parameters as observer specific. We argue that the von Kries component reflects the action of a temporal adaptation mechanism, while the crispening component describes the action of the instantaneous, purely spatial mech-anism most appropriately labeled simultaneous colour contrast. An interesting consequence of this view is that traditional ideas about the general characteristics of simultaneous contrast must be considered as misleading. According to Kirschmann’s 4th law, for instance, the simultaneous contrast effect should increase with increasing saturation of the surround, but crispening predicts the converse. Based on this reasoning, we offer a plausible explanation for the mixed evidence on the validity of Kirschmann’s 4th law. We also argue that simultaneous contrast, the crispening effect, Meyer’s effect and the gamut expansion effect are just different names for the same basic phenomenon.
Title of Thesis:
"... We present a design technique for colours that lower the energy consumption of the display device. Our approach relies on a screen space variant energy model. Guided by perceptual principles, we present three variations of our approach for finding low energy, distinguishable, iso-lightness colours. ..."
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We present a design technique for colours that lower the energy consumption of the display device. Our approach relies on a screen space variant energy model. Guided by perceptual principles, we present three variations of our approach for finding low energy, distinguishable, iso-lightness colours. The first is based on a set of discrete user-named (categorical) colours, which are ordered according to energy consumption. The second optimizes for colours in the continuous CIELAB colour space. The third is hybrid, optimizing for colours in select CIELAB colour subspaces that are associated with colour names. We quantitatively compare our colours with a traditional choice of colours, demonstrating that approximately 45 percent of the display energy is saved. The colour sets are applied to 2D visualization of nominal data and volume rendering of 3D scalar fields. A new colour blending method for volume rendering which preserves hues further improves colour distinguishability.
eDF
, 2011
"... The display of space filling data is still a challenge for the community of visualization. Direct Volume Rendering (DVR) is one of the most important techniques developed to achieve direct perception of such volumetric data. It is based on semi-transparent representations, where the data are accumul ..."
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The display of space filling data is still a challenge for the community of visualization. Direct Volume Rendering (DVR) is one of the most important techniques developed to achieve direct perception of such volumetric data. It is based on semi-transparent representations, where the data are accumulated in a depth-dependent order. However, it produces images that may be difficult to understand, and thus several techniques have been proposed so as to improve its effectiveness, using for instance lighting models or simpler representations (e.g. Maximum Intensity Projection). In this paper we present two perceptual studies that question how DVR meets its goals, in either static or dynamic context. We show that a static representation is highly ambiguous, even in simple cases, but this can be counterbalanced by use of dynamic cues, i.e. motion parallax, provided that the rendering parameters are correctly tuned.
