scholarly journals UNDERWATER IMAGE ENHANCEMENT BASED ON POLARIZATION IMAGING

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 579-585
Author(s):  
L. Shen ◽  
Y. Zhao
Keyword(s):  
Ecological Research ◽  
Underwater Imaging ◽  
High Quality ◽  
Polarization Imaging ◽  
Detection And Tracking ◽  
Imaging Model ◽  
Underwater Image ◽  
Underwater Object ◽  
Image Enhancing ◽  
The Relationship

Abstract. The need of high-quality underwater imaging is obviously required in many underwater applications. For example, underwater archaeology, underwater ecological research, underwater object detection and tracking. This paper presents a joint enhancing and denoising scheme for an image taken in underwater conditions. Conventional image enhancing methods may amplify the noise depending on the distance and density of the particles in the water. To suppress the noise and improve the enhancement performance, an imaging model is modified by adding the process of amplifying the noise in underwater conditions. This model offers depth-chromaticity compensation regularization for the transmission map and chromaticity-depth compensation regularization for enhancing the image. The proposed iterative underwater image enhancing method with polarization uses these two joint regularization schemes and the relationship between the transmission map and enhanced irradiance image. The transmission map and irradiance image are used to promote each other. To verify the effectiveness of the algorithm, polarizing images of different scenes in different conditions are collected. Different algorithms are applied to the original images. Experimental results demonstrate that the proposed scheme increases visibility in extreme conditions without amplifying the noise.

scholarly journals Underwater image enhancement algorithm based on dark channel prior and underwater imaging model

2021 ◽  
Vol 336 ◽  
pp. 06033
Author(s):  
Zhengping Sun ◽  
Fubing Li ◽  
Yuying Yang
Keyword(s):  
Image Enhancement ◽  
Dark Channel Prior ◽  
Underwater Imaging ◽  
Low Contrast ◽  
Underwater Environment ◽  
Imaging Model ◽  
Underwater Image ◽  
Dark Channel ◽  
Color Compensation ◽  
Enhancement Method

The main reason for the degradation of the underwater image is the light absorption and scattering. The images are captured in the underwater environment often have some problems such as loss of image information, low contrast, and color distortion. In order to solve the above problems, this paper proposes an image enhancement method for the underwater environment. With the help of the underwater imaging model and dark channel prior theory, a new idea of adding transmission correction and color compensation to G and B color channels is proposed. Experimental results show that, compared with the traditional methods, this method has a better effect on the underwater image with less color deviation.

Compensatory Coping Through the Extension of Working Hours

2019 ◽  
Vol 63 (3) ◽  
pp. 115-128 ◽  
Author(s):  
Maie Stein ◽  
Sylvie Vincent-Höper ◽  
Nicole Deci ◽  
Sabine Gregersen ◽  
Albert Nienhaus
Keyword(s):  
Job Demands ◽  
Working Hours ◽  
Well Being ◽  
Leader Member Exchange ◽  
Workplace Health ◽  
High Quality ◽  
Data Analyses ◽  
Member Exchange ◽  
The Relationship ◽  
Advance Knowledge

Abstract. To advance knowledge of the mechanisms underlying the relationship between leadership and employees’ well-being, this study examines leaders’ effects on their employees’ compensatory coping efforts. Using an extension of the job demands–resources model, we propose that high-quality leader–member exchange (LMX) allows employees to cope with high job demands without increasing their effort expenditure through the extension of working hours. Data analyses ( N = 356) revealed that LMX buffers the effect of quantitative demands on the extension of working hours such that the indirect effect of quantitative demands on emotional exhaustion is only significant at low and average levels of LMX. This study indicates that integrating leadership with employees’ coping efforts into a unifying model contributes to understanding how leadership is related to employees’ well-being. The notion that leaders can affect their employees’ use of compensatory coping efforts that detract from well-being offers promising approaches to the promotion of workplace health.

IMPLEMENTASI METODE RETINEX UNTUK MENINGKATKAN KUALITAS CITRA UNDERWATER

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Bainun Harahap
Keyword(s):  
Water Environment ◽  
Repair Process ◽  
Image Process ◽  
Two Dimensional ◽  
Two Dimensional Image ◽  
Underwater Image ◽  
Object Search ◽  
Image Improvement ◽  
Underwater Object

Digital imagery is a two-dimensional image process through a digital computer that is used to manipulate and modify images in various ways. Photos are examples of two-dimensional images that can be processed easily. Each photo in the form of a digital image can be processed through certain software devices. In the water environment, light factors greatly influence the results of image quality obtained. With the deepening of underwater shooting, the results obtained will be the darker the quality of the underwater image. Underwater imagery is widely used as an object in various activities such as underwater habitat mapping, underwater environment monitoring, underwater object search. Uneven lighting and colors that tend to be bluish and runny. One of the factors that influence the recognition results in pattern recognition is the quality of the image that is inputted. The image acquired from the source does not always have good quality. The process of improvement in digital images that experience interference in lighting and exposure to sunlight. The lighting repair process uses the retinex method and will compare the quality of the two methods later. Until later the results of both methods can be seen which is better. Retinex method can produce image improvement with high performance.Keywords: Digital Cintra, Underwater, Matlab Retinex Method

scholarly journals Underwater Image Restoration via Non-Convex Non-Smooth Variation and Thermal Exchange Optimization

2021 ◽  
Vol 9 (6) ◽  
pp. 570
Author(s):  
Qingliang Jiao ◽  
Ming Liu ◽  
Pengyu Li ◽  
Liquan Dong ◽  
Mei Hui ◽  
...  
Keyword(s):  
Image Restoration ◽  
Qualitative And Quantitative Analysis ◽  
Formation Model ◽  
High Quality ◽  
Thermal Exchange ◽  
Qualitative And Quantitative ◽  
Smooth Variation ◽  
Underwater Image ◽  
Dark Channel

The quality of underwater images is an important problem for resource detection. However, the light scattering and plankton in water can impact the quality of underwater images. In this paper, a novel underwater image restoration based on non-convex, non-smooth variation and thermal exchange optimization is proposed. Firstly, the underwater dark channel prior is used to estimate the rough transmission map. Secondly, the rough transmission map is refined by the proposed adaptive non-convex non-smooth variation. Then, Thermal Exchange Optimization is applied to compensate for the red channel of underwater images. Finally, the restored image can be estimated via the image formation model. The results show that the proposed algorithm can output high-quality images, according to qualitative and quantitative analysis.

scholarly journals An exploration of the relationship between recruitment communication and foraging in stingless bees

2021 ◽  
Author(s):  
Robbie I’Anson Price ◽  
Francisca Segers ◽  
Amelia Berger ◽  
Fabio S Nascimento ◽  
Christoph Grüter
Keyword(s):  
Stingless Bees ◽  
Sugar Content ◽  
Social Information ◽  
Food Resources ◽  
Food Sources ◽  
Foraging Strategies ◽  
High Quality ◽  
Recruitment Communication ◽  
Eusocial Bees ◽  
The Relationship

Abstract Social information is widely used in the animal kingdom and can be highly adaptive. In social insects, foragers can use social information to find food, avoid danger or choose a new nest site. Copying others allows individuals to obtain information without having to sample the environment. When foragers communicate information they will often only advertise high quality food sources, thereby filtering out less adaptive information. Stingless bees, a large pantropical group of highly eusocial bees, face intense inter- and intra-specific competition for limited resources, yet display disparate foraging strategies. Within the same environment there are species that communicate the location of food resources to nest-mates and species that do not. Our current understanding of why some species communicate foraging sites while others do not is limited. Studying freely foraging colonies of several co-existing stingless bee species in Brazil, we investigated if recruitment to specific food locations is linked to (1) the sugar content of forage, (2) the duration of foraging trips and (3) the variation in activity of a colony from one day to another and the variation in activity in a species over a day. We found that, contrary to our expectations, species with recruitment communication did not return with higher quality forage than species that do not recruit nestmates. Furthermore, foragers from recruiting species did not have shorter foraging trip durations than those from weakly-recruiting species. Given the intense inter- and intraspecific competition for resources in these environments, it may be that recruiting species favour food resources that can be monopolised by the colony rather than food sources that offer high-quality rewards.

scholarly journals Underwater Image Enhancement Based on Multi-Scale Fusion and Global Stretching of Dual-Model

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 595
Author(s):  
Huajun Song ◽  
Rui Wang
Keyword(s):  
Image Enhancement ◽  
Poor Performance ◽  
Weight Coefficient ◽  
Color Contrast ◽  
Dual Model ◽  
Spatial Cues ◽  
Multi Scale ◽  
Imaging Model ◽  
Underwater Image ◽  
Enhancement Method

Aimed at the two problems of color deviation and poor visibility of the underwater image, this paper proposes an underwater image enhancement method based on the multi-scale fusion and global stretching of dual-model (MFGS), which does not rely on the underwater optical imaging model. The proposed method consists of three stages: Compared with other color correction algorithms, white-balancing can effectively eliminate the undesirable color deviation caused by medium attenuation, so it is selected to correct the color deviation in the first stage. Then, aimed at the problem of the poor performance of the saliency weight map in the traditional fusion processing, this paper proposed an updated strategy of saliency weight coefficient combining contrast and spatial cues to achieve high-quality fusion. Finally, by analyzing the characteristics of the results of the above steps, it is found that the brightness and clarity need to be further improved. The global stretching of the full channel in the red, green, blue (RGB) model is applied to enhance the color contrast, and the selective stretching of the L channel in the Commission International Eclairage-Lab (CIE-Lab) model is implemented to achieve a better de-hazing effect. Quantitative and qualitative assessments on the underwater image enhancement benchmark dataset (UIEBD) show that the enhanced images of the proposed approach achieve significant and sufficient improvements in color and visibility.

scholarly journals An Underwater Image Enhancement Algorithm Based on Generative Adversarial Network and Natural Image Quality Evaluation Index

2021 ◽  
Vol 9 (7) ◽  
pp. 691
Author(s):  
Kai Hu ◽  
Yanwen Zhang ◽  
Chenghang Weng ◽  
Pengsheng Wang ◽  
Zhiliang Deng ◽  
...  
Keyword(s):  
Image Quality ◽  
Image Enhancement ◽  
Quality Evaluation ◽  
High Efficiency ◽  
Natural Image ◽  
High Quality ◽  
Generative Adversarial Network ◽  
Image Quality Evaluation ◽  
Adversarial Network ◽  
Underwater Image

When underwater vehicles work, underwater images are often absorbed by light and scattered and diffused by floating objects, which leads to the degradation of underwater images. The generative adversarial network (GAN) is widely used in underwater image enhancement tasks because it can complete image-style conversions with high efficiency and high quality. Although the GAN converts low-quality underwater images into high-quality underwater images (truth images), the dataset of truth images also affects high-quality underwater images. However, an underwater truth image lacks underwater image enhancement, which leads to a poor effect of the generated image. Thus, this paper proposes to add the natural image quality evaluation (NIQE) index to the GAN to provide generated images with higher contrast and make them more in line with the perception of the human eye, and at the same time, grant generated images a better effect than the truth images set by the existing dataset. In this paper, several groups of experiments are compared, and through the subjective evaluation and objective evaluation indicators, it is verified that the enhanced image of this algorithm is better than the truth image set by the existing dataset.

The Study on Formaldehyde Emission of Composite Floor and Activated Carbon Adsorption on Formaldehyde

2011 ◽  
Vol 243-249 ◽  
pp. 4956-4959
Author(s):  
Jian Chao Hao ◽  
Hui Fen Liu ◽  
Dong Ling Wei ◽  
Li Jun Shi ◽  
Jun Li Li ◽  
...  
Keyword(s):  
Activated Carbon ◽  
Kinetic Equation ◽  
Formaldehyde Emission ◽  
Order Kinetic ◽  
Activated Carbon Adsorption ◽  
High Quality ◽  
Carbon Adsorption ◽  
Airtight Chamber ◽  
The Relationship ◽  
Order Kinetic Equation

The relationship between formaldehyde emission and time was researched and a mathematical model was developed which describes the variation of formaldehyde with time in the airtight chamber. It was found that high quality composite floor was in line with 0-order kinetic equation and low quality composite floor was in line with 1-order kinetic equation. Besides, the effect of activated carbon adsorption on formaldehyde was studied and the result showed that activated carbon had poor adsorption on formaldehyde for weak van der waals force.

scholarly journals Feedback Environment and Creativity in Education Organizations

2015 ◽  
Vol 3 (2) ◽  
pp. 121
Author(s):  
Ying-Leh Ling ◽  
Fairuz Ismail ◽  
Abdul Ghani Kanesan Abdullah
Keyword(s):  
Quantitative Study ◽  
Positive Relationship ◽  
Pearson Correlation ◽  
Study Data ◽  
Educational Organizations ◽  
Feedback Environment ◽  
High Quality ◽  
Significant Difference ◽  
Inferential Analysis ◽  
The Relationship

This study aims to examine the relationship between feedback environment practices and creativity in the educational organizations. This study is a quantitative study. A total of 40 polytechnic students from Polytechnic Kuching Sarawak are randomly selected to participate in this study. Data were obtained using a set of questionnaire consisting of three parts. The data obtained were analyzed descriptively and inferentially. Inferential analysis involves <em>t</em> test and Pearson correlation. The findings have shown that the level of feedback environment based on students' perception is high. Simultaneously, the level of creativity among the students is also high. The findings indicated that there is no significant difference in feedback environment between genders. Furthermore, the study also showed a significant and positive relationship between feedback environment and students’ creativity. The results of this study have several implications directly to the formation of high-quality students as feedback environment and students’ creativity are interrelated and inseparable in educational organizations.

scholarly journals Role of Restored Underwater Images in Underwater Imaging Applications

2021 ◽  
Vol 4 (4) ◽  
pp. 96
Author(s):  
Jarina Raihan A ◽  
Pg Emeroylariffion Abas ◽  
Liyanage C De Silva
Keyword(s):  
Machine Learning ◽  
Image Classification ◽  
Feature Detection ◽  
Sea Water ◽  
Learning Algorithm ◽  
Underwater Imaging ◽  
Underwater Image ◽  
Common Problems ◽  
Restoration Method

Underwater images are extremely sensitive to distortion occurring in an aquatic underwater environment, with absorption, scattering, polarization, diffraction and low natural light penetration representing common problems caused by sea water. Because of these degradation of quality, effectiveness of the acquired images for underwater applications may be limited. An effective method of restoring underwater images has been demonstrated, by considering the wavelengths of red, blue, and green lights, attenuation and backscattering coefficients. The results from the underwater restoration method have been applied to various underwater applications; particularly, edge detection, Speeded Up Robust Feature detection, and image classification that uses machine learning. It has been shown that more edges and more SURF points can be detected as a result of using the method. Applying the method to restore underwater images in image classification tasks on underwater image datasets gives accuracy of up to 89% using a simple machine-learning algorithm. These results are significant as it demonstrates that the restoration method can be implemented on underwater system for various purposes.

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