Visibility Improvement Research Articles

Visibility improvement in relation to turbidity and distance, and application to docking

Recently, autonomous underwater vehicles (AUVs) are being used in many applications. There is a limitation for underwater vehicle’s operation that takes a longer duration than the power capacity of underwater vehicles. Since underwater battery recharging station is supposed to be installed in the deep-sea bottom, the deep-sea docking experiments cannot avoid turbidity and dark environment. In this study, we propose a newly designed active 3D marker to improve the visibility of the 3D marker. A docking experiment apparatus was built. Two kinds of the 3D marker were used in the experiment, which were the active (light) and passive (non-light) 3D markers. The experimental results show the active 3D marker can be more recognizable in turbidity and dark environment than the passive 3D marker.

Quantifying the Influences of PM2.5 and Relative Humidity on Change of Atmospheric Visibility over Recent Winters in an Urban Area of East China

Fine particulate matters (PM2.5) and relative humidity (RH) in the ambient atmosphere are the leading anthropogenic and natural factors changing atmospheric horizontal visibility. Based on the analysis of environmental and meteorological data observed over 2013–2019 in Nanjing, an urban area in East China, this study investigated the influences of PM2.5 and RH on atmospheric visibility changes over recent years. The visibility had significantly negative correlations with the PM2.5 concentrations and RH changes. The nonlinear relationships existed between PM2.5 concentrations and visibility, as well as between RH and visibility, with the inflection points in the atmospheric visibility changes. The PM2.5 inflection concentrations were 81.0 μg m−3, 76.0 μg m−3, 49.0 μg m−3, and 33.0 μg m−3, respectively, for the RH ranges of RH < 60%, 60% ≤ RH < 80%, 80% ≤ RH < 90%, and RH ≥ 90%, indicating that the improvement of visibility with reducing PM2.5 concentrations could be more difficult under the humid meteorological condition. The visibility changes were most sensitive to PM2.5 concentrations in the RH range of 60–80% in this urban area of East China. The relative contributions of natural factor RH and anthropogenic factor PM2.5 to variations of wintertime atmospheric visibility were quantified with 54.3% and 45.7%, respectively, revealing an important role of natural factor RH in the change of atmospheric visibility in the urban area of East Asian monsoon region.

Current Challenges in Visibility Improvement in Southern China

Stringent emission controls effectively brought down particulate mass concentrations by >30% in the North China Plain (NCP) and Pearl River Delta (PRD) regions. However, the low-visibility (<10 km)...

Advance computer analysis of magnetic resonance imaging (MRI) for early brain tumor detection

Purpose The brain tumor grows inside the skull and interposes with regular brain functioning. The tumor growth may possibly result in cancer at a later stage. The early detection of brain tumor is crucial for successful treatment of fatal disease. The tumor presence is normally detected by Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) images. The MRI/CT images are highly complex and involve huge data. This requires highly tedious and time-consuming process for detection of small tumors for the neurologists. Thus, there is a need to develop an effective and less time-consuming imaging technique for early detection of brain tumors. Materials and Methods This paper mainly focuses on early detecting and localizing the brain tumor region using segmentation of patient's MRI images. The Matlab software experiments are performed on a set of fifteen tumorous MRI images. In the proposed work, four image segmentation modalities namely watershed transform, k-means clustering, thresholding and Fuzzy C Means Clustering techniques with median filtering have been implemented. Results The results are verified by quantitative comparison of results in terms of image quality evaluation parameters-Entropy, standard deviation and Naturalness Image Quality Evaluator. A remarkable rise in the entropy and standard deviation values has been noticed. Conclusions The watershed transform segmentation with median filtering yields the best quality brain tumor images. The noteworthy improvement in visibility of the MRI images may highly increase the possibilities of early detection and successful treatment of brain tumor disease and thereby assists the clinicians to decide the precise therapies.

Síntese e Caracterização de Material Híbrido Luminescente à Base de Sílica para Revelação de Impressões Digitais Latentes

As impressões digitais são os vestígios mais frágeis encontrados em locais de crime e requerem um aprimoramento da visibilidade. Com isso, a revelação de impressões digitais latentes requer materiais que possibilitem um salto na qualidade, fornecendo alta efiiência e contraste. Desta forma, este trabalho reporta a síntese de um híbrido orgânico-inorgânico com propriedades luminescentes intensas capazes de revelar impressões latentes que assegurem a qualidade necessária para posterior identifiação através dos pontos característicos. Os resultados demonstram que devido à alta emissão fotoluminescente do material sintetizado, foi possível obter a visualização de cristas bem defiidas, levando a identifiação técnica de vários pontos característicos.

CT performance of compact X-ray source with small focal spot using a 950 keV linear accelerator

A 950 keV X-ray source with small focal spot using a linear accelerator has been developed. By installing a focusing mechanism of electron beam, smaller focal spot (0.3 mm in FWHM of the line spread function) is successfully achieved at 950 keV. 9.3 GHz (X-band) radio frequency is used for accelerating electrons in order to make the size of X-ray source smaller, compared to lower radio frequency such as 3.0 GHz (S-band). Size and weight of the developed X-ray source are W 600 mm × D 800 mm × H 500 mm and 230 kg, respectively. Clearer transmission images using a rectangular groove sample are obtained with small spot setup, compared to conventional one. CT images are also obtained for an engine block, and we demonstrated that advantage of 950 keV X-ray source for CT imaging such as improvement of interior visibility and decrease of artefact, compared to a 450 kV X-ray source. Therefore, we are convinced that this 950 keV X-ray source is widely useful for industrial non-destructive inspection of large structures, because of compactness, high transmission ability and spatial resolution.

THE ISSUE OF ROAD VISIBILITY AND ROAD TRAFFIC SAFETY

One of the most difficult problems faced by drivers at night is road visibility and difficulty in seeing obstacles in a timely manner. Many night-time accidents occur on roads with no artificial lighting, especially outside built-up areas. In 2014, in order to improve road safety, a provision for the obligatory use of reflective elements by pedestrians outside built-up areas at night was introduced. However, the exact parameters of these reflective elements (in particular the color, size and location) were not specified, which may have an impact on pedestrian safety. This article compares a car driver’s range of visibility when pedestrians are equipped with different colors of a reflective element, examining the influence of different colors on safety. The analysis shows that, despite the similar technical properties of the same reflective elements, their color contributed to the improvement of visibility, and thus road safety. An experiment conducted in real road conditions testing yellow and orange reflective elements proved that the yellow reflective element significantly improved the range of the driver’s perception.

Real-time 3D Imaging Interface of Micro-targets for Depth Visibility Improvement in Cell Manipulation

Real-time 3D Imaging Interface of Micro-targets for Depth Visibility Improvement in Cell Manipulation

Multi-Objective Adaptable Atmospheric Light and Depth Map Quantization Level Dehazing With CSA

Outdoor natural images captured in turbid weather are subject to produce low visibility which may cause fatal problem in computer vision applications. Single image visibility improvement is the most difficult of all model used in visibility improvement and mostly depends on restoration based optical image formation model. Existing dehazing techniques estimate atmospheric light (AL) and transmission by some prior information. In this work, we examined the strength of the Cuckoo Search Algorithm(CSA) in tuning a new multi-objective image performance function PCS for adaptable dehazing which estimates and balance between noise, contrast and geometrical information of image . Two parameters, AL and Otsu’s quantisation thresholding level in Depth Map (DM), are optimised with levy steps in search space of CSA to produce best dehazed image . GT O-Haze, DerainNet, Frida synthetic dataset have been used for evaluations and our method is compared with ten state-of-the art methods qualitatively and qualitatively for dehazing obtaining satisfactory results.

Determination of optimal virtual monochromatic energy level for target delineation of brain metastases in radiosurgery using dual-energy CT.

Determination of the optimal energy level of virtual monochromatic image (VMI) for brain metastases in contrast-enhanced dual-energy CT (DECT) for radiosurgery and assessment of the subjective and objective image quality of VMI at the optimal energy level. 20 patients (total of 42 metastases) underwent contrast-enhanced DECT. Spectral image analysis of VMIs at energy levels ranging from 40 to 140 keV in 1 keV increments was performed to determine the optimal VMI (VMIopt) as the one corresponding to the highest contrast-to-noise ratio (CNR) between brain parenchyma and the metastases. The objective and subjective values of VMIopt were compared to those of the VMI with 120 kVp equivalent, defined as reference VMI (VMIref, 77 keV). The objective measurement parameters included mean HU value and SD of tumor and brain parenchyma, absolute lesion contrast (LC), and CNR. The subjective measurements included five-point scale assessment of "overall image quality" and "tumor delineation" by three radiation oncologists. The VMI at 63 keV was defined as VMIopt. The LC and CNR of VMIopt were significantly (p < 0.01) higher than those of VMIref (LC: 37.4 HU vs 24.7 HU; CNR: 1.1 vs 0.8, respectively). Subjective analysis rated VMIopt significantly (p < 0.01) superior to VMIref with respect to the overall image quality (3.2 vs 2.9, respectively) and tumor delineation (3.5 vs 2.9, respectively). The VMI at 63 keV derived from contrast-enhanced DECT yielded the highest CNR and improved the objective and subjective image quality for radiosurgery, compared to VMIref. This paper investigated for the first time the optimal energy level of VMI in DECT for brain metastases. The findings will lead to improvement in tumor visibility with optimal VMI and consequently supplement accuracy delineation of brain metastases.

Coarse co-phasing method based on slope of visibility-enhanced dispersed fringe pattern for segmented telescope

Dispersed fringe sensing (DFS) is a promising strategy to bring segmented primary mirror into in-phase for large-aperture segmented telescope. Conventional intensity-based piston extraction methods show operational complexity due to the spectral calibration and poor sensing accuracy for large piston error because of the terrible visibility resulting from the dense fringe modulation. In order to overcome these disadvantages, a visibility improvement technique based on side-lobe enhancement and a slope-based piston extraction algorithm are developed. By scaling up the side lobes in 2-D spectrum of dispersed fringe pattern (DFP), the visibility of DFP could be greatly improved. At the same time, by theoretical analysis, the slope of dispersed fringe is not sensitive to the spectral non-uniformity of the broadband source, thus, the introduced piston extraction algorithm avoids the procedure of spectral calibration. Numerical experiment is conducted to demonstrate its feasibility and accuracy. It provides an efficient, alternative solution to large-scale piston sensing via dispersed fringe sensor.

533 Effect of Pronase on Visibility Scores During Upper Endoscopy: Systematic Review and Meta-Analysis

INTRODUCTION: Pronase is a proteolytic enzyme that helps in removal of mucous when used during the endoscopic examination by mucolytic activity. The increase in visibility during upper endoscopy and endoscopic ultrasound examination leads to identification of early cancerous lesions in the stomach.Different studies have reported varied results for using pronase as a pre-medication to improve visibility. We conducted a systematic review and meta-analysis to assess the improvement in visibility after pre-medication with Pronase in Upper endoscopy. METHODS: We performed a systematic search of multiple databases through May 2019 to identify studies reporting on the use of Pronase and outcomes in terms of visibility scores in upper endoscopy. Pooled visibility scores for different parts of the stomach were obtained. Heterogeneity was assessed by I2 statistics. RESULTS: Seven studies with a total of 2431 patients were included in the final analysis. The mean age ranged from 47 to 61 years with 44% males. majority of the studies were based out of single center data. The dose of pronase used was 20000 units in majority of the studies. Medication administration time varied. Four studies administered pronase 10 minutes before procedure, three studies administered it 20 minutes before procedure and one study used it 30 min before the procedure. Visibility scoring was done based on a scale of 1 to 4, 1 being best possible visualization. The pooled visibility score for the gastric antrum with pronase was 1.42 (95% CI: 1.2-1.6, I2 = 99); for fundus was 1.17 (95% CI: 1.1-1.2, I2 = 67.5); for lower gastric body was 1.46 (95% CI: 1.3-1.7, I2=94.5); and for upper gastric body was 1.68 (95% CI: 1.4-2, I2 = 97.3). Significant heterogeneity was noted in the analysis. CONCLUSION: Based on this meta-analysis the pooled visibility scores appear to be near one which is the ideal score.The optimal time of administration (pre-procedure drink or intraprocedural flushes) and the effect of pronase in improving detection of early cancerous lesion should be determined in future well controlled large studies.

Climate change, increasing forest fire incidence, and the value of visibility: evidence from British Columbia, Canada

Climate change may increase the occurrence and severity of forest fires, leading to worsening wildfire seasons. More frequent burn events would have various effects due to increased haze and smoke, including a greater incidence of impacts on human health and reduced or impaired visibility. In areas such as the Lower Fraser Valley of British Columbia, which prides itself on panoramic mountain and city views, individuals may be willing to pay to address deteriorating visibility conditions arising from wildfires or other sources. However, studies consistently show that any attempt to ask individuals how much they are willing to pay to improve local visibility will be confounded with the benefits of improving local health conditions. We used a discrete choice experiment to estimate the value of potential improvements in local visibility in the Lower Fraser Valley, but we included the consideration of health effects and found that these two attributes were indeed linked. As human preferences are rarely homogeneous, we also considered heterogeneity in respondents’ preferences for increases in the number of improved-visibility days versus healthy days. Finally, we applied our results to estimate the value of damages from visibility disruptions related to wildfire smoke from 2002 to 2018 in the Lower Fraser Valley.

WLMS-based Transmission Refined Self-Adjusted No Reference Weather Independent Image Visibility Improvement

ABSTRACTSingle image dehazing is an ill-posed, challenging issue out of several dehazing techniques due to its limited information. Transmission map is a crucial reference to retrieve the dehazed output. An attempt has been taken to remove artefacts in the depth map of the hazy image with Weighted Least Mean Square-based edge preserved smoothing technique which in turn estimate artifact-free transmission map. Original bright, clear, and natural image radiance is restored using refined transmission estimation and image recovery optical model developed and it has been showed to be effective in comparison with the state-of-the art techniques. Extensive experiments (quality and quantity) validate that the proposed technique is computationally less expensive, simple, and efficient. Computational complexity is linear or quasi-linear depending on the size of the image, O(n) or O(nlogn). In either case complexity is still lower than other state-of-the art techniques. The proposed algorithm is adaptable to remove different types of haze. Visible distance, as well as extinction coefficient of the medium of the hazy and recovered images, are also measured.

In-Depth Analysis of Contemporary Grayscale Image Dehazing Methods: A Comprehensive Review

Since the fog results in loss and color distortion in an image under poor weather circumstances, an efficient image defogging algorithm is required for retrieving various details in an image and hence recovery of a true color information for visibility improvement. In this paper several state-of-art techniques designed by different researchers towards solving this problem in order to enhance the image by improving the existing present day approaches have been presented. Various enhancements in this area are suggested to increase the value of quality parameters which leads to the better defogged image and hence decreases the road accidents existing day by day. Several intelligent techniques including Q-Deep learning methods with other computer vision algorithms have been suggested to improve upon the visibility of the foggy scene. Finally, the whole review have been concluded by pointing out the several advantages and shortcomings of the existing literature.

Underwater Image Restoration Based on a Parallel Convolutional Neural Network

Restoring degraded underwater images is a challenging ill-posed problem. The existing prior-based approaches have limited performance in many situations due to the reliance on handcrafted features. In this paper, we propose an effective convolutional neural network (CNN) for underwater image restoration. The proposed network consists of two paralleled branches: a transmission estimation network (T-network) and a global ambient light estimation network (A-network); in particular, the T-network employs cross-layer connection and multi-scale estimation to prevent halo artifacts and to preserve edge features. The estimates produced by these two branches are leveraged to restore the clear image according to the underwater optical imaging model. Moreover, we develop a new underwater image synthesizing method for building the training datasets, which can simulate images captured in various underwater environments. Experimental results based on synthetic and real images demonstrate that our restored underwater images exhibit more natural color correction and better visibility improvement against several state-of-the-art methods.

Country of Origin as a Constraint to Internationalization

Objective – Globalization has enabled the increase of competitiveness and opportunities for companies to sell their goods to worldwide consumers. Due to the wider range of products offered and increasing similarity of those products, the country of origin becomes an important variable when studying the evaluation process of foreign products. The origin of a product acts as a mark of quality, which ultimately influences the purchase intentions of consumers. When negative, this may act as a constraint on internationalization, making it difficult to accept a product from a certain origin. There is, therefore, a gap in how companies can mitigate and overcome a negative country of origin effect (COE). This study seeks to fill this gap and suggest strategies to overcome this issue. Methodology/Technique –The methodology applied in this study is the Grounded Theory. The data was collected from interviews with Portuguese entities, so different cases can be compared and discussed. Although Portugal’s image has changed over time, there remains a stigma associated with it. The most recent financial and political crisis has damaged the perception of Portugal in the international sphere, hence, it has been selected for the formation of a negative COE. Findings and Novelty – Some firms currently have existing strategies to resist the negative effect of country of origin, such as improvement of brand awareness, credibility and international visibility. To achieve that, companies must adopt a wide set of strategies which involve both defensive and offensive approaches. Type of Paper: Empirical Keywords: Country of Origin; Country of Origin Effect; Internationalization; Constraints; Grounded theory. Reference to this paper should be made as follows: Meneses, R.; Santos, S. 2019. Country of Origin as a Constraint to Internationalization, J. Bus. Econ. Review 4 (2): 105 – 113 https://doi.org/10.35609/jber.2019.4.2(5) JEL Classification: F6, F60, F69.

Visibility improvement and mass segmentation of mammogram images using quantile separated histogram equalisation with local contrast enhancement

In this work, the authors develop a working software-based approach named ‘linearly quantile separated histogram equalisation-grey relational analysis’ for mammogram image (MI). This approach improves overall contrast (local and global) of given MI and segments breast-region with a specific end goal to acquire better visual elucidation, examination, and grouping of mammogram masses to help radiologists in settling on more precise choices. The fundamental commitment of this work is to demonstrate that results of good quality of breast-region segmentation can be accomplished from basic breast-region segmentation if the input image has good contrast and a better interpretation of hidden details. They have evaluated the proposed strategy for MIAS-MIs. Experimental results have shown that the proposed approach works better than state-of-the-art.

Fog removal in images using improved dark channel prior and contrast limited adaptive histogram equalization

It is necessary to perform fog removal from an image based on the estimation of depth to increase the visibility of a scene. In this paper, we propose a new algorithm to eradicate fog from images in which fog is defined as a state or cause of perplexity or confusion with respect to the image. It runs at high speed and simultaneously minimizes the halo-artifact with a new median operator in dark channel prior. The proposed method is based on Guided Filter for transmission-map refinement and Contrast Limited Adaptive Histogram Equalization (CLAHE) for visibility improvement. It preserves small details while remaining robust against density of fog, and recovers scene contrast simultaneously. Guided filter improved the transmission map acquired from Median dark channel prior (MDCP), which is an improvement of the Dark Channel Prior DCP by the use of median operation. All of the parameters used in our method are data driven. The quality of algorithm has been validated on several types of fog-degraded images where considerable variation in contrast and illumination exists. Moreover, its performance is compared with the other state-of-the-art methods. The experimental results indicate that the proposed method effectively restores the color and contrast of scene as well as produces satisfactory information in homogeneous fog. It outperforms the existing fog removal methods for run time computational time and other evaluation metrics for rating of visibility enhancement. The proposed method conserves small details part of the image when outstanding vigorous against concentration of fog, and recuperate scene contrast instantaneously. It controls at a high speed than the existing approaches and can diminish the halo effect.

Visibility Improvement in Expressway Tunnels by Optimizing the Color Temperature and Light Distribution of the Pulse-operated LED Luminaires

Visibility Improvement in Expressway Tunnels by Optimizing the Color Temperature and Light Distribution of the Pulse-operated LED Luminaires