Underwater Illumination Research Articles

An Improved Underwater Visual SLAM through Image Enhancement and Sonar Fusion

To enhance the performance of visual SLAM in underwater environments, this paper presents an enhanced front-end method based on visual feature enhancement. The method comprises three modules aimed at optimizing and improving the matching capability of visual features from different perspectives. Firstly, to address issues related to insufficient underwater illumination and uneven distribution of artificial light sources, a brightness-consistency recovery method is proposed. This method employs an adaptive histogram equalization algorithm to balance the brightness of images. Secondly, a method for denoising underwater suspended particulates is introduced to filter out noise from images. After image-level processing, a combined underwater acousto–optic feature-association method is proposed, which associates acoustic features from sonar with visual features, thereby providing distance information for visual features. Finally, utilizing the AFRL dataset, the improved system incorporating the proposed enhancement methods is evaluated for its performance against the OKVIS framework. The system achieves a better trajectory estimation accuracy compared to OKVIS and demonstrates robustness in underwater environments.

Ultra Broad‐Band Excitable Organic–Inorganic Copper(I) Halides: Large‐Scale Synthesis, Outstanding Stability, and Highly Efficient White Light‐Emitting Diodes Application

AbstractOrganic–inorganic copper(I) halides (OICHs) have recently attracted great attentions for their unique optoelectronic properties. However, most of them have poor stability and narrow excitation in UV region, which seriously hinder their applications in efficient white light‐emitting diodes (WLEDs). Herein, 0D (C19H18P)2Cu4I6 with super broad‐band excitation (300–500 nm) and yellow emission with the absolute photoluminescence quantum yield of 87.4% is synthesized in a quantity of gram scale. Specifically, (C19H18P)2Cu4I6 possesses exceptional thermal‐, photo‐, air‐stability, and can maintain efficient emission even if soaked in water, ethyl acetate, and isopropanol over 30 days. WLEDs with remarkable color stability under various driven currents are fabricated using 450, 400, 365, and 310 nm LED chips. The ideal WLEDs based on single (C19H18P)2Cu4I6 by 450 nm LED chip presents high color rendering index of 86.7, and outstanding luminous efficiency of 90 lm W−1. To the best of the knowledge, this is the highest value that is achieved based on single‐component OICHs using blue light chip. This work not only promotes the prospect of OICHs in WLEDs but also significantly broadens their application in special lighting fields, such as underwater illumination.

Underwater light source changes microecosystem constructed by Vallisneria spinulosa Yan for water restoration: Efficiency of water purification, characteristics of growth, and rhizosphere

Submerged macrophytes are effective in ecological restoration of water bodies polluted by nitrogen and phosphorus, and its restoration capacity depends on underwater illumination condition. This study explored the influencing mechanism of illumination on Vallisneria spinulosa Yan (V. spinulosa Yan) for water restoration. Addition of underwater light source increased the total nitrogen, ammonia nitrogen, total phosphorus, and phosphate removal loads of the V. spinulosa Yan growth system by 61.5, 39.2, 8.5, and 5.0 mg m−2 d-1, respectively. Meanwhile, the growth of V. spinulosa Yan was obviously promoted, even with high water turbidity. Although the biological nitrogen removal processes were inhibited by adding underwater light source, the growth of V. spinulosa Yan can be significantly improved, thus enhancing the efficiency of water purification via the absorption of nitrogen and phosphorus by V. spinulosa Yan. This study provides a theoretical foundation and technical support for application of submerged macrophytes in ecological water restoration.

Lightweight underwater image adaptive enhancement based on zero-reference parameter estimation network

Underwater images suffer from severe color attenuation and contrast reduction due to the poor and complex lighting conditions in the water. Most mainstream methods employing deep learning typically require extensive underwater paired training data, resulting in complex network structures, long training time, and high computational cost. To address this issue, a novel ZeroReference Parameter Estimation Network (Zero-UAE) model is proposed in this paper for the adaptive enhancement of underwater images. Based on the principle of light attenuation curves, an underwater adaptive curve model is designed to eliminate uneven underwater illumination and color bias. A lightweight parameter estimation network is designed to estimate dynamic parameters of underwater adaptive curve models. A tailored set of non-reference loss functions are developed for underwater scenarios to fine-tune underwater images, enhancing the network’s generalization capabilities. These functions implicitly control the learning preferences of the network and effectively solve the problems of color bias and uneven illumination in underwater images without additional datasets. The proposed method examined on three widely used real-world underwater image enhancement datasets. Experimental results demonstrate that our method performs adaptive enhancement on underwater images. Meanwhile, the proposed method yields competitive performance compared with state-of-the-art other methods. Moreover, the Zero-UAE model requires only 17K parameters, minimizing the hardware requirements for underwater detection tasks. What’more, the adaptive enhancement capability of the Zero-UAE model offers a new solution for processing images under extreme underwater conditions, thus contributing to the advancement of underwater autonomous monitoring and ocean exploration technologies.

Weighted multi-error information entropy based you only look once network for underwater object detection

Underwater object detection is considered as one of the most challenging issues in computer vision. In this paper, a weighted multi-error information entropy based YOLO (You Only Look Once) network is proposed to address underwater illumination noise affecting the detection accuracy. First, underwater illumination is essentially structural and non-uniform, and it is modeled as an independent and piecewise identical distribution, which is a generic noise model to describe the complex underwater illuminating environment and accommodates the traditional Gaussian distribution as a special case. Second, assisted by the proposed illumination noise model, a minimum weighted error entropy criterion, which is an information-theoretic learning method, is introduced into the loss function of YOLO network, and then the network parameters are trained and optimized to improve the detection performance. Furthermore, a multi-error processing strategy is simultaneously used to handle vector errors during information back-propagation in order to accelerate convergence. Experiments on underwater object detection datasets including URPC2018, URPC2019 and Enhanced dataset, show the proposed weighted multi-error information entropy based YOLOv8 network gets mean average precision (MAP) of 88.7%, 91.8% and 96.7% respectively, and average frames per second (FPS) of 116.6. These two evaluation metrics are better than the baseline YOLOv8 and the existing advanced non-YOLO approaches by at least 5.2% and 5.3% respectively. The results verify the effectiveness and superiority of the proposed network for underwater object detection in complex underwater environment.

Underwater power compensated white light source based on synthetic white laser

The semiconductor white laser light source is used as a light source for underwater illumination. The required standard color temperature of white light is obtained at the underwater target surface. We studied the power compensation of a synthetic white laser source and its application to underwater illumination. First, the power ratios of the red (638 nm), green (520 nm), and blue (450 nm) lasers at a color temperature of 6500 K were obtained by using chromaticity theory. Next, the three-color and synthetic white laser parameters were obtained with transmission distance, according to the exponential attenuation characteristics of different light in clear water and seawater medium. The three-color laser power at the output was compensated, and the underwater target illumination surface reached the standard 6500 K color temperature of the white laser, improving the illumination. Finally, an experimental system for underwater white laser illumination based on power compensation was established. The errors between experimental and theoretical results of color temperature and illuminance are no more than 0.43% and 22.15%. This power-compensated synthetic white laser light source has both the advantages of long-range underwater detection and the spectral advantages of LED white light sources. The white laser light source meets specific requirements by compensating for power and optimizing white light characteristics for underwater lighting applications.

Non-uniform illumination underwater image enhancement via events and frame fusion.

Absorption and scattering by aqueous media can attenuate light and cause underwater optical imagery difficulty. Artificial light sources are usually used to aid deep-sea imaging. Due to the limited dynamic range of standard cameras, artificial light sources often cause underwater images to be underexposed or overexposed. By contrast, event cameras have a high dynamic range and high temporal resolution but cannot provide frames with rich color characteristics. In this paper, we exploit the complementarity of the two types of cameras to propose an efficient yet simple method for image enhancement of uneven underwater illumination, which can generate enhanced images containing better scene details and colors similar to standard frames. Additionally, we create a dataset recorded by the Dynamic and Active-pixel Vision Sensor that includes both event streams and frames, enabling testing of the proposed method and frame-based image enhancement methods. The experimental results conducted on our dataset with qualitative and quantitative measures demonstrate that the proposed method outperforms the compared enhancement algorithms.

Implementation of an automated workflow for image-based seafloor classification with examples from manganese-nodule covered seabed areas in the Central Pacific Ocean

Mapping and monitoring of seafloor habitats are key tasks for fully understanding ocean ecosystems and resilience, which contributes towards sustainable use of ocean resources. Habitat mapping relies on seafloor classification typically based on acoustic methods, and ground truthing through direct sampling and optical imaging. With the increasing capabilities to record high-resolution underwater images, manual approaches for analyzing these images to create seafloor classifications are no longer feasible. Automated workflows have been proposed as a solution, in which algorithms assign pre-defined seafloor categories to each image. However, in order to provide consistent and repeatable analysis, these automated workflows need to address e.g., underwater illumination artefacts, variances in resolution and class-imbalances, which could bias the classification. Here, we present a generic implementation of an Automated and Integrated Seafloor Classification Workflow (AI-SCW). The workflow aims to classify the seafloor into habitat categories based on automated analysis of optical underwater images with only minimal amount of human annotations. AI-SCW incorporates laser point detection for scale determination and color normalization. It further includes semi-automatic generation of the training data set for fitting the seafloor classifier. As a case study, we applied the workflow to an example seafloor image dataset from the Belgian and German contract areas for Manganese-nodule exploration in the Pacific Ocean. Based on this, we provide seafloor classifications along the camera deployment tracks, and discuss results in the context of seafloor multibeam bathymetry. Our results show that the seafloor in the Belgian area predominantly comprises densely distributed nodules, which are intermingled with qualitatively larger-sized nodules at local elevations and within depressions. On the other hand, the German area primarily comprises nodules that only partly cover the seabed, and these occur alongside turned-over sediment (artificial seafloor) that were caused by the settling plume following a dredging experiment conducted in the area.

A Pulse Delay Control Method by External Trigger to Underwater Illumination

Aiming at the problem of high precision pulse synchronization control in digital signal processing, we proposed an external trigger synchronization control method by double-layer hierarchical delay. The method consists of hardware circuit and control algorithm. The hardware circuit employs the main control unit and the digital delay unit, in which the main control unit makes the coordination between the digital delay unit and the peripheral circuit, and the two-layer digital delay unit performs multiple fixed period delay operation according to the instruction of the main control unit. The control algorithm adopts the two-layer hierarchical control mode, decomposes the total delay time according to the two-layer delay precision, and performs the combined delay in the two-layer digital delay unit successively. The delay result achieves a fixed delay of less than 40 ns, a delay step of 0.25 ns and a delay range of less than 1000 ns. The method adopts the combination of hardware and software to realize the external trigger double-layer hierarchical delay synchronization control, which has the characteristics of high delay step and pulse width adjustment accuracy and small cumulative delay error. It is suitable for the application scenarios of lidar echo signal and ultra-wide spectrum power source synthesis.

Automatic Semantic Segmentation of Benthic Habitats Using Images from Towed Underwater Camera in a Complex Shallow Water Environment

Underwater image segmentation is useful for benthic habitat mapping and monitoring; however, manual annotation is time-consuming and tedious. We propose automated segmentation of benthic habitats using unsupervised semantic algorithms. Four such algorithms––Fast and Robust Fuzzy C-Means (FR), Superpixel-Based Fast Fuzzy C-Means (FF), Otsu clustering (OS), and K-means segmentation (KM)––were tested for accuracy for segmentation. Further, YCbCr and the Commission Internationale de l’Éclairage (CIE) LAB color spaces were evaluated to correct variations in image illumination and shadow effects. Benthic habitat field data from a geo-located high-resolution towed camera were used to evaluate proposed algorithms. The Shiraho study area, located off Ishigaki Island, Japan, was used, and six benthic habitats were classified. These categories were corals (Acropora and Porites), blue corals (Heliopora coerulea), brown algae, other algae, sediments, and seagrass (Thalassia hemprichii). Analysis showed that the K-means clustering algorithm yielded the highest overall accuracy. However, the differences between the KM and OS overall accuracies were statistically insignificant at the 5% level. Findings showed the importance of eliminating underwater illumination variations and outperformance of the red difference chrominance values (Cr) in the YCbCr color space for habitat segmentation. The proposed framework enhanced the automation of benthic habitat classification processes.

Detektovanje podvodnih metalnih objekata pomoću veštačke inteligencije i zaštita od korozije predmeta od mekog čelika korišćenih u podvodnoj studiji - studija slučaja - Deo A - detektovanje podvodnih metalnih objekata pomoću veštačke inteligencije

Due to the importance of underwater exploration in the development and utilization of deep-sea resources, underwater autonomous operation is more and more important to avoid the dangerous high-pressure deep-sea environment. For underwater autonomous operation, intelligent computer vision is the most important technology. In an underwater environment, weak illumination and low-quality image enhancement, as a pre-processing procedure, is necessary for underwater vision. In this paper, introduced Deep learning-based Underwater Metal object detection using input Image data by using several step to improve the model performance. In this experimentation we are using TURBID dataset 100 images to validate the performance. And also we compare the performance result by given the input images in different validation level. In first input image is initially preprocessed and that images is given to the KFCM-Segmentation. The segmented images are given to the DWT Extraction to extract the features from those images. And finally the Convolution Neural Network (CNN) is used to classify the images to detect the objects. Also this proposed model attained the classification accuracy of 98.83%. This method is much suitable for detect the objects in underwater robotically. Metallic parts of machines of ships or airplanes may submerge in sea water. They may undergo corrosion when they come in contact with sea water which contains 3.5% sodium chloride. This is most commonly responsible for the corrosive nature of the seawater. The robots made of materials such as mild steel may also undergo corrosion when they come in contact with sea water, while is search. If a paint coating is given, it will control the corrosion of these proposed materials. Hence this work is undertaken. Mild steel is coated with Asian guard red paint. Corrosion resistance of mild in 3.5% sodium chloride solution is measured before coating and after coating by electrochemical studies such as polarization study and AC impedance spectra. The corrosion inhibition efficiency offered by red paint to mild steel in 3.5% sodium chloride is 99.98%.

Dynamic spectral compensation of white LEDs in underwater illumination

Based on Mie scattering and Monte Carlo ray tracing method, the spectral transmission behavior of visible light in the seawater is estimated. Its optical model is constructed for the fast and accurate prediction of light quality changes of phosphor-based white LED underwater illumination with distance. Because of this, we propose to add a dual-wavelength LED to the original white LED, which would perform spectrum compensation at each illumination distance to restore its good light quality. The result shows that such a dynamic light source can successfully maintain correlated color temperature at 6000 K and color rendering index above 80 under different underwater illumination distances.

Optimization of LED fishing lamp allocation based on numerical modeling in Pacific saury fishery

Artificial light plays an important role in commercial light fisheries as a means to attract fish, such as the Pacific saury and squid. To gain an insight into the optimal allocation of light-emitting diode (LED) fishing lamps in the Pacific saury fishery, we present a mathematical illumination model to describe the illumination characteristics of LED modules installed at different angles. The validity of the numerical model was evaluated against the results of an optical experiment and statistical analysis. The results indicated that the agreement between observed and modeled data was good, with a mean error of 8.83%, and that the light distribution varied greatly depending on the angle. The light intensity of the LED module was distributed in the form of a series of concentric circles in the light field. With increasing angle, the maximum illumination decreased and moved away from the light source; also, the horizontally illuminated distance increased but the rate of increase gradually decreased. The illumination attenuation showed different modes between angles after passing the position at which there was maximum illumination. These results could help to further reveal the effects of LED fishing lamp allocations (e.g., installation angle, height, and interval) on underwater illumination characteristics for the optimization of the onboard lighting system and the regulation of the power of fishing lights in the future.

Weibull Tone Mapping for Underwater Imagery

Imagery is a preferred tool for environmental surveys within marine environments, particularly in deeper waters, as it is nondestructive compared to traditional sampling methods. However, underwater illumination effects limit its use by causing extremely varied and inconsistent image quality. Therefore, it is often necessary to pre-process images to improve visibility of image features and textures, and standardize their appearance. Tone mapping is a simple and effective technique to improve contrast and manipulate the brightness distributions of images. Ideally, such tone mapping would be automated, however we found that existing techniques are inferior when compared to custom manipulations by image annotators (biologists). Our own work begins with the observation that these userdefined tonal manipulations are quite variable, though on average, are fairly smooth, gentle waving operations. To predict user-defined tone maps we found it sufficed to approximate the brightness distributions of input and user adjusted images by Weibull distributions and then solve for the tone curve which matched these distributions from input to output. Experiments demonstrate that our Weibull Tone Mapping (WTM) method is strongly preferred over traditional automated tone mappers and weakly preferred over the users' own tonal adjustments.

Spectral Irradiance Distribution in Underwater Light Field Generated by an LED Light Source

Yang, P.; Wu, Z.; Chen, Y.; Guo, Y.; Zhang, P., and Song, H., 2020. Spectral irradiance distribution in underwater light field generated by an LED light source. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 453–457. Coconut Creek (Florida), ISSN 0749-0208.Artificial underwater illumination has a wide range of applications in coastal zone research, marine engineering, marine resource exploration and development, and marine ecological environment monitoring. In this article, the distribution of spectral irradiance has been discussed for an underwater light field generated by an underwater LED light source. Theoretical representations of the spectral irradiance have been derived according to physical principles and underwater spectral irradiance measurement have been accrued out along the optical axis of the light source and in the vertical plane perpendicular to the optical axis. Experimental results show that the spectral irradiance along the optical axis of the light source decays with respect to the distance, following the law of square attenuation and exponential attenuation. The irradiance in the vertical plane approximately matches the Gaussian distribution.

Enhancement of wastewater treatment with underwater light: Efficiency and micro-ecosystem alterations in the open aerobic reactor of living machine

The source separation and decentralised treatment technology for domestic wastewater is an important method to improve sewage treatment rates and water reuse. The Living Machine (LM) system is a widely applied decentralised domestic wastewater treatment technology. In order to enhance the black water (toilet water) treatment performance, an underwater lamp was placed in the open aerobic reactor of the LM system, and treatment efficiency and micro-ecosystem changes with different light intensities were studied in this research. Compared to the control reactor (C), removal efficiencies of ammonia, total nitrogen (TN), and total phosphorus (TP) were increased from 22.07%, 16.03%, and 13.81% to 42.20%, 22.82%, and 17.20%, respectively, in the underwater light reactor (L) with an average intensity of 2083.00 LX, and COD removal was not obviously effected. The species and numbers of algae and the species of zooplankton and other aquatic animals were increased sharply in L, but their number did not fit a linear relation with light intensity. The bacteria group was prominently changed in L, whereas Malikia_spinosa, Emticicia_sediminis, and Rhodocyclaceae_bacterium_MORI13 were increased, and Rhodocyclaceae_bacterium_ICHIDE18 was obviously decreased. Although underwater illumination enhanced the wastewater reactor performance of the LM open aerobic reactor, further research is needed to learn more about the process optimization and relative mechanism.

Research and Design of Marine Underwater LED Illumination System Based on Sliding Mode Variable Structure

Pan, P., 2019. Research and design of marine underwater LED illumination system based on sliding mode variable structure. In: Li, L.; Wan, X., and Huang, X. (eds.), Recent Developments in Practices and Research on Coastal Regions: Transportation, Environment and Economy. Journal of Coastal Research, Special Issue No. 98, pp. 239–242. Coconut Creek (Florida), ISSN 0749-0208.This paper introduces the working characteristics of an underwater LED illumination system and analyzes the driving power supply of the LED illumination system and the application of its control mode. In addition, the sliding mode variable structure control (SMVSC) method of constant-current power supply for an underwater LED illumination system is studied and designed in this paper. By choosing appropriate sliding mode surface function and control parameters, the constant-current control of the LED load is realized. Finally, to verify the effectiveness and superiority of the SMVSC method design for the LED illumination system, the SMVSC method is modeled and simulated using MATLAB software and compared with the conventional PI control method, which proves the validity of the design.

Underwater Image Recovery Using Structured Light

Structured lighting techniques have increasingly been employed in underwater imaging. Except for the limitation in underwater illumination, the desire of underwater image acquisition comes from the applicability of removal of the back scattered light, the critical problem of underwater imaging, using structured lighting techniques. This paper presents an approach for underwater image recovery using structured light and CCD camera. By integrating the scanned frame images, we generate an integration image which can be formulated as the convolution of the surface albedo and the illumination function. Thus, underwater image acquisition is addressed as an optimization problem of image recovery and resolved by deconvolution, rather than the traditional geometric manipulation of frame tiling. The significance of the proposed method is that the forward scattering effect in the recovered image is fully eliminated by the integration operation and collection of the forward scattered light enhances the total imaging energy. By means of the structured lighting technique, an algorithm of using virtual aperture to limit the field of view is proposed to eliminate the back scattered light in frame images. Concerned with applicability of using the broad lighting pattern in structured light systems, the coded structured light with binary pseudo-random sequence is introduced, by which the high-frequency details in image recovery can be preserved through deconvolution. The results of underwater experiments are given.

Investigation of the mechanisms of sea spray generation induced by wind-wave interaction in laboratory conditions

The paper presents the results of investigations of the mechanisms of spray of droplets generation within wind wave interaction obtained under laboratory conditions on the High-speed Wind-Wave Flume of the Institute of Applied Physics of the Russian Academy of Sciences. For the research, a multi-angle high-speed video system used together shadow method, including underwater illumination. The results allowed for the classification of mechanismsleading to the formation of droplets. Three main types of phenomena responsible for the generation of the spume droplets near the wave crest were specified: breakage of liquid ligaments, bursting of large submerged bubbles, and bag breakup. The last and less known mechanism claims to be dominant for high wind speeds and it was described in detail.

10-m 9.51-Gb/s RGB laser diodes-based WDM underwater wireless optical communication.

The availability of the underwater wireless optical communication (UWOC) based on red (R), green (G) and blue (B) lights makes the realization of the RGB wavelength division multiplexing (WDM) UWOC system possible. By properly mixing RGB lights to form white light, the WDM UWOC system has prominent potentiality for simultaneous underwater illumination and high-speed communication. In this work, for the first time, we experimentally demonstrate a 9.51-Gb/s WDM UWOC system using a red-emitting laser diode (LD), a single-mode pigtailed green-emitting LD and a multi-mode pigtailed blue-emitting LD. By employing 32-quadrature amplitude modulation (QAM) orthogonal frequency division multiplexing (OFDM) modulation in the demonstration, the red-light, the green-light and the blue-light LDs successfully transmit signals with the data rates of 4.17 Gb/s, 4.17 Gb/s and 1.17 Gb/s, respectively, over a 10-m underwater channel. The corresponding bit error rates (BERs) are 2.2 × 10-3, 2.0 × 10-3 and 2.3 × 10-3, respectively, which are below the forward error correction (FEC) threshold of 3.8 × 10-3.