Diverging Trends in the Visual Appearance of Fired Clay in Roman Architecture: ‘Campana Plaques’ and Terracotta Façades

Image enhancement (IE) is very important in the field where visual appearance of an image is the main. Image enhancement is the process of improving the image in such a way that the resulting or output image is more suitable than the original image for specific task. With the help of image enhancement process the quality of image can be improved to get good quality images so that they can be clear for human perception or for the further analysis done by machines.Image enhancement method enhances the quality, visual appearance, improves clarity of images, removes blurring and noise, increases contrast and reveals details. The aim of this paper is to study and determine limitations of the existing IE techniques. This paper will provide an overview of different IE techniques commonly used. We Applied DWT on original RGB image then we applied FHE (Fuzzy Histogram Equalization) after DWT we have done the wavelet shrinkage on Three bands (LH, HL, HH). After that we fuse the shrinkage image and FHE image together and we get the enhance image.

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Distribution of Mercury in Lake St. Clair and the St. Clair River Sediments

Water Quality Research Journal ◽

10.2166/wqrj.1989.002 ◽

1989 ◽

Vol 24 (1) ◽

pp. 1-22 ◽

Cited By ~ 3

Author(s):

Alena Mudroch ◽

K. Hill

Keyword(s):

Organic Matter ◽

Sediment Cores ◽

River Sediments ◽

Size Fraction ◽

Mineralogical Composition ◽

Recent Sediment ◽

Geochemical Composition ◽

Visual Appearance ◽

Decaying Wood ◽

Relationship Of

Abstract Sediment cores were collected in Lake St. Clair in 1985 and in the St. Clair River in 1986 to investigate the horizontal and vertical distribution and association of Hg in the sediments. A layer of recent sediment up to about 35 cm thick was differentiated by the geochemical composition and visual appearance from the underlying glacial-lacustrine deposits. The concentration of Hg in the surficial sediments in Lake St. Clair was lower in 1985 (<0.025 to 1.200 µg/g) than that found in 1974 (<0.20 to 3.00 µg/g). Up to 8.30 µg/g of Hg were found in the sediments collected from the nearshore area at Sarnia, Ontario, in the St. Clair River in 1986. The concentrations of Hg ranged from 5.05 to 16.00 µg/g in different sand-sized fractions (0.063 to 0.350 mm) of the sediment. The concentration of Hg was 17.80 µg/g in the silt-clay size fraction (<0.063 mm). No relationship was found between the concentration of organic matter and Hg, and the concentration of silica and Hg in the St. Clair River sediments. The results indicated a relationship of Hg with particles of different mineralogical composition. Up to 3.72 µg/g Hg was found in the surface sediment in Chenal Ecarte. The greatest concentration of Hg (13.15 µg/g) existed in the 0.350 mm particle size fraction, which consisted mainly of small pieces of decaying wood. A good relationship was found between the concentration of Hg and organic matter in the sediment at this area.

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Fig Plant Segmentation from Aerial Images Using a Deep Convolutional Encoder-Decoder Network

Remote Sensing ◽

10.3390/rs11101157 ◽

2019 ◽

Vol 11 (10) ◽

pp. 1157 ◽

Cited By ~ 8

Author(s):

Jorge Fuentes-Pacheco ◽

Juan Torres-Olivares ◽

Edgar Roman-Rangel ◽

Salvador Cervantes ◽

Porfirio Juarez-Lopez ◽

...

Keyword(s):

Precision Agriculture ◽

Image Data ◽

Ground Truth ◽

Aerial Images ◽

Aerial Image ◽

Data Set ◽

Visual Appearance ◽

Aerial Robots ◽

Lighting Conditions ◽

Convolutional Encoder

Crop segmentation is an important task in Precision Agriculture, where the use of aerial robots with an on-board camera has contributed to the development of new solution alternatives. We address the problem of fig plant segmentation in top-view RGB (Red-Green-Blue) images of a crop grown under open-field difficult circumstances of complex lighting conditions and non-ideal crop maintenance practices defined by local farmers. We present a Convolutional Neural Network (CNN) with an encoder-decoder architecture that classifies each pixel as crop or non-crop using only raw colour images as input. Our approach achieves a mean accuracy of 93.85% despite the complexity of the background and a highly variable visual appearance of the leaves. We make available our CNN code to the research community, as well as the aerial image data set and a hand-made ground truth segmentation with pixel precision to facilitate the comparison among different algorithms.

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098 Effects of Metameric Display-Light on Alertness, Vigilance and Melatonin

SLEEP ◽

10.1093/sleep/zsab072.097 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A40-A41

Author(s):

Isabel Schöllhorn ◽

Oliver Stefani ◽

Manuel Spitschan ◽

Robert Lucas ◽

Christian Cajochen

Keyword(s):

Statistical Power ◽

Light Exposure ◽

Vigilance Task ◽

Ongoing Study ◽

Swiss National Science Foundation ◽

Visual Appearance ◽

Salivary Melatonin ◽

Subjective Alertness ◽

Psychomotor Vigilance ◽

Circadian Physiology

Abstract Introduction Light emitted from visual displays can acutely increase alertness, improve cognitive performance and suppress melatonin in the evening. Here we tested the influence of different melanopic irradiance levels emitted by a metameric display setting on alertness, vigilance and salivary melatonin levels. Methods In an ongoing study, 37 healthy, male participants have so far completed a 2-week study protocol. Volunteers were assigned to one of four luminance groups which differed in brightness levels (27 cd/m2 - 280 cd/m2). Illuminance ranged between 7 and 85 lx. Within the four groups each volunteer was exposed to a low melanopic (LM) and a high melanopic condition (HM). The LM and HM differed in melanopic irradiance (ca. 3-fold change), but matched in terms of cone excitation (metamers). Before, during and after the light exposure, volunteers performed a psychomotor vigilance task (PVT). Subjective alertness and melatonin levels were continuously measured in half-hourly intervals throughout scheduled wakefulness in the 17-h in lab study. Results Preliminary analysis yielded an overall alerting response in the HM vs. the LM condition (p<0.05) concomitant with a trend of reduced melatonin levels in HM vs. LM (p=0.08). So far, we could not observe a difference in PVT performance for HM and LM (Reaction time responses between 100 and 500 ms). Since we are still lacking statistical power in the ongoing study, we cannot yet satisfactorily interpret interaction effects between melanopic condition and brightness. Conclusion Our data indicate that rather low brightness levels of high melanopic display light impacts alertness and melatonin levels in the evening. Thus, metameric low melanopic display light may be a promising method to attenuate activating properties of evening light on circadian physiology without affecting visual appearance. Support (if any) This project is funded by the Swiss National Science Foundation (SNSF).

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Hidden by bias: how standard psychophysical procedures conceal crucial aspects of peripheral visual appearance

Scientific Reports ◽

10.1038/s41598-021-83325-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Fazilet Zeynep Yildirim ◽

Daniel R. Coates ◽

Bilge Sayim

Keyword(s):

Visual Perception ◽

Line Pair ◽

Crucial Aspect ◽

Time And Space ◽

Contextual Modulation ◽

Visual Appearance ◽

Single Time ◽

Visual Periphery ◽

Contextual Stimuli ◽

Biased Perception

AbstractThe perception of a target depends on other stimuli surrounding it in time and space. This contextual modulation is ubiquitous in visual perception, and is usually quantified by measuring performance on sets of highly similar stimuli. Implicit or explicit comparisons among the stimuli may, however, inadvertently bias responses and conceal strong variability of target appearance. Here, we investigated the influence of contextual stimuli on the perception of a repeating pattern (a line triplet), presented in the visual periphery. In the neutral condition, the triplet was presented a single time to capture its minimally biased perception. In the similar and dissimilar conditions, it was presented within stimulus sets composed of lines similar to the triplet, and distinct shapes, respectively. The majority of observers reported perceiving a line pair in the neutral and dissimilar conditions, revealing ‘redundancy masking’, the reduction of the perceived number of repeating items. In the similar condition, by contrast, the number of lines was overestimated. Our results show that the similar context did not reveal redundancy masking which was only observed in the neutral and dissimilar context. We suggest that the influence of contextual stimuli has inadvertently concealed this crucial aspect of peripheral appearance.

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Photograph Based Evaluation of Consumer Expectation on Healthiness, Fullness, and Acceptance of Sandwiches as Convenience Food

Foods ◽

10.3390/foods10051102 ◽

2021 ◽

Vol 10 (5) ◽

pp. 1102

Author(s):

Purificación García-Segovia ◽

Mª Jesús Pagán-Moreno ◽

Amparo Tárrega ◽

Javier Martínez-Monzó

Keyword(s):

Interaction Effect ◽

Online Survey ◽

Age Groups ◽

Nominal Group Technique ◽

Nominal Group ◽

Visual Appearance ◽

Consumer Expectation ◽

Preference Mapping ◽

Consumer Experiences ◽

And Cluster Analysis

Sandwiches are the most common “casual-food” consumed by all age groups in Spain. Due to the importance of visual appearance to promote unplanned or impulse buying, foodservice and hospitality companies focus on improving the visual impression of their food menus to create an expectation that satisfies both sensory and hedonic consumer experiences. To provide a list of attributes about the visual appearance of sandwiches, 25 students were recruited from a university and were invited to participate in two nominal group technique (NGT) sessions. To understand whether a sandwiches’ appearance can influence the expectation of consumers, 259 participants completed an online survey specially designed from the results of the NGT sessions. Data were analyzed using conjoint, internal preference mapping and cluster analysis; the interaction effect by gender was also studied. The conjoint results indicate that visual perception about the filling (vegetal or pork based) plays the most key role overall in consumer expectation. When consumers choose vegetables as the filling, the consumers’ perceived sandwiches as healthier, but the pork filling was perceived as more attractive and satiating. Interaction effect by gender was observed in filling when females perceived pork filling as less healthy than vegetable. By acceptance, consumers were segmented into three groups. The first cluster (n = 80) selected the pork filling. The smaller group (cluster 3, n = 36) prioritized the vegetal filling, and the most numerous cluster 2 (n = 140) liked sandwiches with multigrain bread. These results may help companies to build tailor-made marketing strategies to satisfy consumer segments.

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Influence of visual appearance on consumer perception of spiciness in kimchi

Journal of Sensory Studies ◽

10.1111/joss.12659 ◽

2021 ◽

Author(s):

Seo‐yeong Chon ◽

Sora Yoon ◽

Jeehyoung Ha ◽

Mina K. Kim

Keyword(s):

Consumer Perception ◽

Visual Appearance

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Visual Appearance of Oil on the Sea

Journal of Marine Science and Engineering ◽

10.3390/jmse9010097 ◽

2021 ◽

Vol 9 (1) ◽

pp. 97

Author(s):

Merv Fingas

Keyword(s):

Water Surface ◽

Oil Spills ◽

Discharge Rate ◽

Physical Explanation ◽

Visual Appearance ◽

Oil In Water ◽

Other Information ◽

Surface Discharges ◽

Oil Emulsions ◽

Spilled Oil

The visual appearance of oil spills at sea is often used as an indicator of spilled oil properties, state and slick thickness. These appearances and the oil properties that are associated with them are reviewed in this paper. The appearance of oil spills is an estimator of thickness of thin oil slicks, thinner than a rainbow sheen (<3 µm). Rainbow sheens have a strong physical explanation. Thicker oil slicks (e.g., >3 µm) are not correlated with a given oil appearance. At one time, the appearance of surface discharges from ships was thought to be correlated with discharge rate and vessel speed; however, this approach is now known to be incorrect. Oil on the sea can sometimes form water-in-oil emulsions, dependent on the properties of the oil, and these are often reddish in color. These can be detected visually, providing useful information on the state of the oil. Oil-in-water emulsions can be seen as a coffee-colored cloud below the water surface. Other information gleaned from the oil appearance includes coverage and distribution on the surface.

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Non-Local and Multi-Scale Mechanisms for Image Inpainting

Sensors ◽

10.3390/s21093281 ◽

2021 ◽

Vol 21 (9) ◽

pp. 3281

Author(s):

Xu He ◽

Yong Yin

Keyword(s):

Markov Random Fields ◽

Receptive Fields ◽

Image Inpainting ◽

Long Distance ◽

Visual Appearance ◽

Fine Grained ◽

Multi Scale ◽

Non Local ◽

Relationship Of

Recently, deep learning-based techniques have shown great power in image inpainting especially dealing with squared holes. However, they fail to generate plausible results inside the missing regions for irregular and large holes as there is a lack of understanding between missing regions and existing counterparts. To overcome this limitation, we combine two non-local mechanisms including a contextual attention module (CAM) and an implicit diversified Markov random fields (ID-MRF) loss with a multi-scale architecture which uses several dense fusion blocks (DFB) based on the dense combination of dilated convolution to guide the generative network to restore discontinuous and continuous large masked areas. To prevent color discrepancies and grid-like artifacts, we apply the ID-MRF loss to improve the visual appearance by comparing similarities of long-distance feature patches. To further capture the long-term relationship of different regions in large missing regions, we introduce the CAM. Although CAM has the ability to create plausible results via reconstructing refined features, it depends on initial predicted results. Hence, we employ the DFB to obtain larger and more effective receptive fields, which benefits to predict more precise and fine-grained information for CAM. Extensive experiments on two widely-used datasets demonstrate that our proposed framework significantly outperforms the state-of-the-art approaches both in quantity and quality.

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