Estimation of Perceptual Surface Property Using Deep Networks with Attention Models

How we perceive property of surfaces with distinct geometry and reflectance under various illumination conditions is not fully understood. One widely studied approach to understanding perceptual surface property is to derive statistics from images of surfaces with the goal of constructing models that can estimate surface property attributes. This work presents machine learning-based methods to estimate the lightness and glossiness of surfaces. Instead of deriving image statistics and building estimation models on top of them, we use deep networks to estimate the perceptual surface property directly from surface images. We adopt the attention models in our networks, to allow the networks to estimate the surface property based on features in certain parts of images. This approach can rule out image variations due to geometry, reflectance, and illumination when making the estimations. The networks are trained with perceptual lightness and glossiness data obtained from psychophysical experiments. The trained deep networks provide accurate estimations of surface property that correlate well with human perception. The network performances are compared with various image statistics derived for estimation of perceptual surface property

A new marine ciliate, Metaurostylopsis antarctica nov. spec. (Ciliophora, Urostylida) from the Antarctic Ocean

In this study, a new marine urostylid ciliate, Metaurostylopsis antarctica nov. spec. collected from the Antarctic Ocean was investigated using morphological, morphometrical, and molecular methods. Metaurostylopsis antarctica nov. spec. is characterized as follows: slender to ellipsoid form in body shape; two types of cortical granules, ellipsoid large one (type I, yellow-green, 1.5 × 1 μm) in rows along dorsal kineties and cirri, circular small one (type II, colourless, 0.3 μm in diameter) scattered throughout whole body; 19–24 adoral membranelles, 4 frontal cirri, 2–5 frontoterminal cirri, 1 buccal and 2 transverse cirri; 3–5 midventral pairs, 10–15 cirri of midventral row; 1 right and 2 left marginal rows; 3 dorsal kineties; about 43 macronuclear nodules. This new species mainly differs from the congeners by the number of marginal rows (1 vs. 3 or more on right side; 2 vs. 3 or more on left side). In addition, proter’s oral primordium  developed on the right side of the oral cavity (vs. in center of oral cavity), and the rightmost anlage splits into two parts, nam ely, the frontoterminal cirri and a transverse cirrus (vs. only frontoterminal cirri). Inter-specific dissimilarities of the SSU rRNA gene between the congeners range from 3.3 to 4.4%

Particulate matter 10 exposure affects intestinal functionality in both inflamed 2D intestinal epithelial cell and 3D intestinal organoid models

BackgroundA growing body of evidence suggests that particulate matter (PM10) enters the gastrointestinal (GI) tract directly, causing the GI epithelial cells to function less efficiently, leading to inflammation and an imbalance in the gut microbiome. PM10 may, however, act as an exacerbation factor in patients with inflamed intestinal epithelium, which is associated with inflammatory bowel disease.ObjectiveThe purpose of this study was to dissect the pathology mechanism of PM10 exposure in inflamed intestines.MethodsIn this study, we established chronically inflamed intestinal epithelium models utilizing two-dimensional (2D) human intestinal epithelial cells (hIECs) and 3D human intestinal organoids (hIOs), which mimic in vivo cellular diversity and function, in order to examine the deleterious effects of PM10 in human intestine-like in vitro models.ResultsInflamed 2D hIECs and 3D hIOs exhibited pathological features, such as inflammation, decreased intestinal markers, and defective epithelial barrier function. In addition, we found that PM10 exposure induced a more severe disturbance of peptide uptake in inflamed 2D hIECs and 3D hIOs than in control cells. This was due to the fact that it interferes with calcium signaling, protein digestion, and absorption pathways. The findings demonstrate that PM10-induced epithelial alterations contribute to the exacerbation of inflammatory disorders caused by the intestine.ConclusionsAccording to our findings, 2D hIEC and 3D hIO models could be powerful in vitro platforms for the evaluation of the causal relationship between PM exposure and abnormal human intestinal functions

Optimal tone curve characteristics of transparent display for preferred image reproduction

Preferred monitor gamma setting is compared between normal and 10%-transmittance transparent display by simulating indoor lighting condition using LCD monitor. Four test images are manipulated to have 10 different monitor gamma values both for normal and transparent display. Based on 10 observers' judgment, it is found that lower gamma setting is preferred for transparent display than that for normal display. The preferred gamma settings for normal and transparent display have the similar lightness difference between gray levels.open

Pearliness as an Intrinsic Characteristic of Surface

The perceived pearliness values of pink colored UV coated polycarbonate samples having three different pearlescent particle sizes and five different densities are investigated to be compared with the previous study using the similar samples. Each sample"s pearliness is estimated in the viewing both illuminated with D65 using magnitude estimation method. In total twenty-one observers estimate thirty samples in the experiment. The data analysis results show that the perceived pearliness values are mostly affected by the average pearl particle sizes than densities. Also comparison between two independent pearliness data sets shows that number of observers and the number of samples can play an important role to decide the pearliness scale. The conventional color measurement data such as gloss and CIELAB cannot predict the perceived pearliness phenomena. Further research is needed to establish the metric to predict the visual pearliness based on the measurement data

Effects of Black Luminance Level on Image Quality

The image quality is affected by the black luminance level of the image. This research aimed to investigate how low luminance levels are required to maintain image quality. The psychophysical experiment was carried out in a dark room using OLED display. Total of 6 different black luminance levels (0.003, 0.05, 0.1, 0.2, 0.3, and 1 cd/m2 ) were used in the experiment. Total of 20 participants was invited to evaluate the image quality. For the experiment, twelve test images are used and these test images categorized into three groups as dark, medium bright and bright image group by image histogram distribution. Each image is rendered by adjusting six different black luminance levels. Result found that the black level is higher than 0.1 cd/m2, the preference for the image is decreased. The best performance is achieved when the black level is 0.003 cd/m2 , but there is no big difference from 0.1 cd/m2. The final result shows that a change in black level between about 0.003 cd/m2 and 0.1 cd/m2 does not significantly affect image quality

Visual appearance measurement of surfaces containing pearl flakes

The color, gloss, and texture (i.e., pearliness) of 15 glossy samples containing pearl flakes were investigated. Psychophysical experimental data from 21 observers were compared with measurement data. Color measurement data obtained using the CIE D/0 and ASTM E2539-08 multiangle geometry did not predict the overall color appearance variation of pearly samples. Pearly samples have a lower perceived glossiness than non-pearly surfaces with the same level of gloss treatment, but a much higher measured gloss. Pearliness describes the texture of pearly samples well and can be predicted as a function of the pearl flakes??? average size and area coverage measured from magnified surface images. These results suggest that an image statistics approach is required to properly describe the visual appearance of pearly surfaces.close

Perceived Glossiness of Bumpy Surface

The perceived glossiness of 12 flat samples and 18 bumpy samples with various colors and gloss levels is estimated by 13 observers using magnitude estimation technique. Each sample is measured with the gloss-meter as well. It is found that bumpy surface shows lower measured gloss level than flat surface treated with the same level of UV coating. The perceived glossiness of bumpy surface is higher than that of flat surface with low level UV coating treatment while perceived glossiness of bumpy surface is lower than that of flat surface with high level UV coating treatment. This record was migrated from the OpenDepot repository service in June, 2017 before shutting down

Monitor brightness changes under a wide range of surround conditions

Display brightness data were collected under a wide range of surround conditions. A 24 in. (60.96 cm) LCD display was used to generate color stimuli, and a 107 in. (271.78 cm) two-dimensional illuminator was used to generate various surround conditions. The brightness values of the display under 89 monitor-surround-luminance combinations were collected from 10 or 24 observers. The surround ratio, SR, i.e., the luminance ratio between the surround and the monitor, varied from 0 to 90. Based on the collected brightness data, we propose a new c value as the log function of the surround ratio, SR, to improve the performance of the CIECAM02 brightness predictor Q.clos