2017
DOI: 10.1007/978-3-319-56010-6_20
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Image Contrast Measure as a Gloss Material Descriptor

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Cited by 8 publications
(18 citation statements)
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“…However, it has been shown by Anderson and Kim [3] that non-glossy images can also produce similar histograms and image statistics do not fully explain the complex neurophysiological processes of gloss perception (e.g., References [18,32,37]). Other widely studied image metrics that are proposedly related to gloss are contrast [38,39,49,62], sharpness [38,39,49], and coverage area [4,31,38,39] of the highlights. The glossiness of a given material has been demonstrated not to be constant and can vary to a great extent, e.g., across different shapes [39,48,66].…”
Section: Gloss Perceptionmentioning
confidence: 99%
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“…However, it has been shown by Anderson and Kim [3] that non-glossy images can also produce similar histograms and image statistics do not fully explain the complex neurophysiological processes of gloss perception (e.g., References [18,32,37]). Other widely studied image metrics that are proposedly related to gloss are contrast [38,39,49,62], sharpness [38,39,49], and coverage area [4,31,38,39] of the highlights. The glossiness of a given material has been demonstrated not to be constant and can vary to a great extent, e.g., across different shapes [39,48,66].…”
Section: Gloss Perceptionmentioning
confidence: 99%
“…The six distinct dimensions of gloss-specular gloss, contrast gloss, distinctness-of-reflected-image gloss, absence-of-bloom gloss, absenceof-surface-texture gloss, and sheen-have been proposed by Hunter [29] back in 1937. Since then, gloss has been accepted as a surface-related quality, and perception of gloss has been studied in the context of surface scattering models [49,62,71]. Various image cues have been proposed to be used by the HVS for gloss perception (for instance, the total area covered by specular reflections, contrast between specular reflections and surrounding areas, the sharpness of the edges of the specular regions [38,39]).…”
Section: Introductionmentioning
confidence: 99%
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“…Although the Ward model is probably the most used model in material perception studies with simulated surfaces (e.g. [13,22,25,30,44,49,50,60,61,75,78,81,82,92,98,99,101,104,110]), this model was recently shown to be unable to capture some of the perceptually relevant aspects of the physics of relection [38,39]. Thus, we rendered diferent materials based on a slightly more complex model, characterized by ive parameters [19,37,57].…”
Section: Introductionmentioning
confidence: 99%