Underwater Inhomogeneous Light Field Based on Improved Convolutional Neural Net Fish Image Recognition

In this paper, artificial intelligence image recognition technology is used to improve the recognition rate of individual domestic fish and reduce the recognition time, aiming at the problem that it is difficult to easily observe the species and growth of domestic fish in the underwater non-uniform light field environment. First, starting from the image data collected by polarizing imaging technology, this paper uses subpixel convolution reconstruction to enhance the image, uses image translation and fill technology to build the family fish database, builds the Adam-Dropout-CNN (A-D-CNN) network model, and its convolution kernel size is 3 × 3. The maximum pooling was used for downsampling, and the discarding operation was added after the full connection layer to avoid the phenomenon of network overfitting. The adaptive motion estimation algorithm was used to solve the gradient sparse problem. The experiment shows that the recognition rate of A-D-CNN is 96.97% when the model is trained under the domestic fish image database, which solves the problem of low recognition rate and slow recognition speed of domestic fish in non-uniform light field.

Performances of conventional fusion methods evaluated for inland water body observation using GF-1 image

Satellite remote sensing of inland water body requires a high spatial resolution and a multiband narrow spectral resolution, which makes the fusion between panchromatic(PAN) and multi-spectral(MS) images particularly important. Taking the Daquekou section of the Qiantang River as an observation target, four conventional fusion methods widely accepted in satellite image processing, including pan sharpening(PS), principal component analysis(PCA), Gram-Schmidt(GS), and wavelet fusion(WF), are utilized to fuse MS and PAN images of GF-1.The results of subjective and objective evaluation methods application indicate that GS performs the best,followed by the PCA, the WF and the PS in the order of descending. The existence of a large area of the water body is a dominant factor impacting the fusion performance. Meanwhile, the ability of retaining spatial and spectral informations is an important factor affecting the fusion performance of different fusion methods. The fundamental difference of reflectivity information acquisition between water and land is the reason for the failure of conventional fusion methods for land observation such as the PS to be used in the presence of the large water body. It is suggested that the adoption of the conventional fusion methods in the observing water body as the main target should be taken with caution. The performances of the fusion methods need re-assessment when the large-scale water body is present in the remote sensing image or when the research aims for the water body observation.

Image of Landscapes in Ancient Water Towns——Case Study on Zhouzhuang and Tongli of Jiangsu Province

Researchers in several disciplines and fields agree that the image establishing has both perceptual and affecfive evaluations. The paper comparatively analyzes the image of landscapes in ancient water towns held by 1619 tourists after the investigations of Zbouzhuang and Tongli of Jiangsu Province. Based on the elements of the image of urban landscapes, the perceptual/cognitive image of tourist landscapes in water towns is developed including path, node, landmark, important courtyard, district and edge. Particularly the important courtyard plays the great role on the perceptive image of tourists, however, the perceptual/cognitive images of the district and the edge are obviously weak. Meanwhile, the finding showed that the affective images of tourist landscapes in Zhonzhuang differ with those of Tongli by the method of paired comparison. The main reason is that the affective images are influenced by the impressive scenery spots. Furthermore, the commercialization of streets and pollution of rivers are easy to be functioned negatively.

Image-based Water Level Measurement Method under Stained Ruler

This paper propoes the water level measuring method based on the image, while the ruler used to indicate the water level is stained. The contamination of the ruler weakens or eliminates many features which are required for the image processing. However, the feature of the color difference between the ruler and the water surface are firmer on the environmental change compare to the other features. As the color differeaces are embossed, only the region of the ruler is limited to eliminate the noise, and the average image is produced by using several continuous frames. A histogram is then produced on the height axis of the produced intensity average image. Local peaks and local valleys are detected, and the section between the peak and valley which have the greatest change is looked for. The valley point at this very moment is used to detect the water level. The detected water level is then converted to the actual water level by using the mapping table. The proposed method is compared to the ultrasonic based method to evaluate its accuracy and efficiency on the various contaminated environments.

A Thin Cloud Removal Method from Remote Sensing Image for Water Body Identification

In this paper,a thin cloud removal method was put forward based on the linear relationships between the thin cloud reflectance in the channels from 0.4 μm to 1.0 μm and 1.38 μm.Channels of 0.66 μm,0.86 μm and 1.38 μm were chosen to extract the water body information under the thin cloud.Two study cases were selected to validate the thin cloud removal method.One case was applied with the Earth Observation System Moderate Resolution Imaging Spectroradiometer(EOS/MODIS) data,and the other with the Medium Resolution Spectral Imager(MERSI) and Visible and Infrared Radiometer(VIRR) data from Fengyun-3A(FY-3A).The test results showed that thin cloud removal method did not change the reflectivity of the ground surface under the clear sky.To the area contaminated by the thin cloud,the reflectance decreased to be closer to the reference reflectance under the clear sky after the thin cloud removal.The spatial distribution of the water body area could not be extracted before the thin cloud removal,while water information could be easily identified by using proper near infrared channel threshold after removing the thin cloud.The thin cloud removal method could improve the image quality and water body extraction precision effectively.

Automated Extraction for Water Bodies Using New Water Index from Landsat 8 OLI Images

The extraction of water bodies is essential for monitoring water resources,ecosystem services and the hydrological cycle,so analyzing water bodies from remote sensing images is necessary.The water index is designed to highlight water bodies in remote sensing images.We employ a new water index and digital image processing technology to extract water bodies automatically and accurately from Landsat 8 OLI images.Firstly,we preprocess Landsat 8 OLI images with radiometric calibration and atmospheric correction.Subsequently,we apply KT transformation,LBV transformation,AWEI nsh,and HIS transformation to the preprocessed image to calculate a new water index.Then,we perform linear feature enhancement and improve the local adaptive threshold segmentation method to extract small water bodies accurately.Meanwhile,we employ morphological enhancement and improve the local adaptive threshold segmentation method to extract large water bodies.Finally,we combine small and large water bodies to get complete water bodies.Compared with other traditional methods,our method has apparent advantages in water extraction,particularly in the extraction of small water bodies.

Application Research of PETD Combined with MRI Nerve Root Water Imaging in the Minimally Invasive Treatment of LDH

Objective: This study aims to evaluate the safety and efficacy of PETD combined with nerve root water imaging of MRI for the treatment of lumbar disc herniation. Methods: A retrospective review was performed on 62 patients with lumbar disc herniation from March 2019 to March 2021. The study included an experimental group of 30 patients and a control group of 32 patients. The experimental group underwent PETD combined with nerve root water imaging of MRI, while the control group received traditional PETD treatment. The visual analogue scoring method (VAS score), and JOA lumbar spine function score before and after surgery were compared between the two groups, and efficacy was assessed and compared using the MacNab score. Results: The mean operation time was significantly reduced in the experimental group (56.43 ±10.40 minutes) compared to the control group (65.69 ±14.12 minutes). The VAS score was compared between the two groups with preoperative (p = 0.624), one month after surgery (p = 0.325), three months after surgery (p = 0.676), one year after surgery (p = 0.341);The JOA score was compared between the two groups with preoperative (p = 0.961), one month after the surgery (p = 0.266), three months after surgery (p = 0.185), one year after surgery (p = 0.870), they were no significant statistical difference;The efficacy evaluation of the last follow-up Macnab showed that all the 30 patients in the experimental group were excellent, 31 of 32 patients in the control group were excellent, 1 case was good;There was no statistical difference in the comparison between the two groups (p > 0.05). Conclusion: The study concludes that the combined approach of PETD with nerve root water imaging of MRI is a safe, effective, and more efficient alternative to conventional PETD for treating lumbar disc herniation.

Automatic segmentation of gas plumes from multibeam water column images using a U-shape network

Cold seeps are widely developed on the seabed of continental margins and can form gas plumes due to the upward migration of methane-rich fluids.The detection and automatic segmentation of gas plumes are of great significance in locating and studying the cold seep system that is usually accompanied by hydrate layers in the subsurface.A multibeam echo-sounder system(MBES)can record the complete backscatter intensity of the water column,and it is one of the most effective means for detecting cold seeps.However,the gas plumes recorded in multibeam water column images(WCI)are usually blurred due to the interference of the complicated water environment and the sidelobes of the MBES,making it difficult to obtain the effective segmentation.Therefore,based on the existing UNet semantic segmentation network,this paper proposes an AP-UNet network combining the convolutional block attention module and the pyramid pooling module for the automatic segmentation and extraction of gas plumes.Comparative experiments are conducted among three traditional segmentation methods and two deep learning methods.The results show that the AP-UNet segmentation model can effectively suppress complicated water column noise interference.The segmentation precision,the Dice coefficient,and the recall rate of this model are 92.09%,92.00%,and 92.49%,respectively,which are 1.17%,2.10%,and 2.07%higher than the results of the UNet.

A method of remote sensing image water segmentation based on adaptive morphological elliptical structuring elements

The use of visible and infrared remote sensing images to calculate the water area is an effective means to grasp the basic situation of water resources,and water segmentation is the premise of statistics.Generally,the edge features of the water in the remote sensing images are complex.When the traditional morphology is used for image segmentation,it is easy to change the image edge and affect the accuracy of image segmentation because the fixed structuring elements are used to perform morphological operations on the image.To segment water in the remote sensing image accurately,a remote sensing image water segmentation method based on adaptive morphological elliptical structuring elements is proposed.Firstly,the eigenvalue and eigenvector of the image are estimated by linear structure tensor,and the elliptical structuring elements are constructed by the eigenvalue and eigenvector.Then adaptive morphological operations are defined,combining the close operation to eliminate the influence of dark detail noise on water without overstretching the water edge,so that the water edge can be maintained more accurately.Finally,on this basis,the water area can be segmented by gray slice.The experimental results show that the proposed method has higher segmentation accuracy and the average segmentation error is less than 1.43%.

Retrieving chlorophyll content and equivalent water thickness of Moso bamboo(Phyllostachys pubescens) forests under Pantana phyllostachysae Chao-induced stress from Sentinel-2A/B images in a multiple LUTs-based PROSAIL framework

Biochemical components of Moso bamboo(Phyllostachys pubescens)are critical to physiological and ecological processes and play an important role in the material and energy cycles of the ecosystem.The coupled PROSPECT with SAIL(PROSAIL)radiative transfer model is widely used for vegetation biochemical component content inversion.However,the presence of leaf-eating pests,such as Pantana phyllostachysae Chao(PPC),weakens the performance of the model for estimating biochemical components of Moso bamboo and thus must be considered.Therefore,this study considered pest-induced stress signals associated with Sentinel-2A/B images and field data and established multiple sets of biochemical canopy reflectance look-up tables(LUTs)based on the PROSAIL framework by setting different parameter ranges according to infestation levels.Quantitative inversions of leaf area index(LAI),leaf chlorophyll content(LCC),and leaf equivalent water thickness(LEWT)were derived.The scale conversions from LCC to canopy chlorophyll content(CCC)and LEWT to canopy equivalent water thickness(CEWT)were calculated.The results showed that LAI,CCC,and CEWT were inversely related with PPC-induced stress.When applying multiple LUTs,the p-values were<0.01;the R2 values for LAI,CCC,and CEWT were 0.71,0.68,and 0.65 with root mean square error(RMSE)(normalized RMSE,NRMSE)values of 0.38(0.16),17.56μg cm-2(0.20),and 0.02 cm(0.51),respectively.Compared to the values obtained for the traditional PROSAIL model,for October,R2 values increased by 0.05 and 0.10 and NRMSE decreased by 0.09 and 0.02 for CCC and CEWT,respectively and RMSE decreased by 0.35μg cm-2 for CCC.The feasibility of the inverse strategy for integrating pest-induced stress factors into the PROSAIL model,while establishing multiple LUTs under different pest-induced damage levels,was successfully demonstrated and can potentially enhance future vegetation parameter inversion and monitoring of bamboo forest health and ecosystems.

Water Gauge Image Denoising Model Based on Improved Adaptive Total Variation

As an important part of water level warning in water conservancy projects,often due to the influence of environmental factors such as light and stains,the acquired water gauge images have sticky,broken and bright spot conditions,which affect the identification of water gauges.To solve this problem,a water gauge image denoising model based on improved adaptive total variation is proposed.Firstly,the regular term exponent in the adaptive total variational equation is changed to an inverse cosine function;secondly,the differential curvature is used to distinguish the image noise points and increase the smoothing strength at the noise points;finally,according to the characteristics of the gradient mode and adaptive gradient threshold after Gaussian filtering,the New model can adaptively denoise in the smooth area and protect the edge area,so as to have the characteristics of both edge-preserving denoising.The experimental results show that the new model has a great improvement in image vision,higher iteration efficiency and an average increase of 1.6 dB in peak signal-to-noise ratio,and an average increase of 9%in structural similarity,which is more beneficial to practical applications.

Soil Salinity and Soil Water Content Estimation Using Digital Images in Coastal Field:A Case Study in Yancheng City of Jiangsu Province,China

Soil is the essential part for agricultural and environmental sciences,and soil salinity and soil water content are both the important influence factors for sustainable development of agriculture and ecological environment.Digital camera,as one of the most popular and convenient proximal sensing instruments,has its irreplaceable position for soil properties assessment.In this study,we collected 52 soil samples and photographs at the same time along the coast in Yancheng City of Jiangsu Province.We carefully analyzed the relationship between soil properties and image brightness,and found that soil salt content had higher correlation with average image brightness value than soil water content.From the brightness levels,the high correlation coefficients between soil salt content and brightness levels concentrated on the high brightness values,and the high correlation coefficients between soil water content and brightness levels focused on the low brightness values.Different significance levels(P)determined different brightness levels related to soil properties,hence P value setting can be an optional way to select brightness levels as the input variables for modeling soil properties.Given these information,random forest algorithm was applied to develop soil salt content and soil water content inversion models using randomly 70%of the dataset,and the rest data for testing models.The results showed that soil salt content model had high accuracy(R_(v)^(2)=0.79,RMSE_(v)=12 g/kg,and RPD_(v)=2.18),and soil water content inversion model was barely satisfied(R_(v)^(2)=0.47,RMSE_(v)=3.04%,and RPD_(v)=1.38).This study proposes a method of modeling soil properties with a digital camera.Combining unmanned aerial vehicle(UAV),it has potential popularization and application value for precise agriculture and land management.

Water bodies extraction from TM images

Aiming at the problems of high time-consuming, low accuracy and weak versatility of the existing methods of wa- ter extraction based on TM image, this paper combines principal component analysis （PCA） with the modified normalized difference water index （MNDWI） which was improved by XU Han-qiu to construct a false color composite image that could separate water from others easily. This method can realize the water extraction based on TM image by analyzing the spectral characteristics of water in this false color image and establishing a water extraction model. This paper also compares the effi- ciency of this method with MNDWI, （TM2 ＋ TM3） - （TM4 ＋ TM5） and new water index （NWI）, which were applied in the city and mountain of Taiyuan, respectively. The results show that the proposed method can extract water body from TM im- age more rapidly and efficiently and its accuracy is up to 94.03 %. In addition, this method does not require a manual selec- tion threshold, which meets the research reuuirement of high automaticm.

A Review of Particle Image Velocimetry for Fish Migration

Understanding the flow characteristic in fishways is crucial for efficient fish migration. Flow characteristic measurements can generally provide quantitative information of velocity distributions in such passages;Particle Image Velocimetry (PIV) has become one of the most versatile techniques to disclose flow fields in general and in fishways, in particular. This paper firstly gives an overview of fish migration along with fish ladders and then the application of PIV measurements on the fish migration process. The overview shows that the quantitative and detailed turbulent flow information in fish ladders obtained by PIV is critical for analyzing turbulent properties and validating numerical results.

City Image Analysis of Food in Guangzhou-Taking Yamaha Fish Stall as an Example

In the representation system of city image,food has become a huge influence in the process of city image construction.In the construction of“food as the sky”as the city image of Guangzhou,it includes three forms:prototype image,conceptual image,and symbol image.There are several differences in the three forms,and the myth of“eating in Guangzhou”is constructed in the specific visual practice.

Automatic Generation of Water Masks from RapidEye Images

Water is a very important natural resource and it supports all life forms on earth. It is used by humans in various ways including drinking, agriculture and for scientific research. The aim of this research was to develop a routine to automatically extract water masks from RapidEye images, which could be used for further investigation such as water quality monitoring and change detection. A Python-based algorithm was therefore developed for this particular purpose. The developed routine combines three spectral indices namely Simple Ratios (SRs), Normalized Green Index (NGI) and Normalized Difference Water Index (NDWI). The two SRs are calculated between the NIR and green band, and between the NIR and red band. The NGI is calculated by rationing the green band to the sum of all bands in each image. The NDWI is calculated by differencing the green to the NIR and dividing by the sum of the green and NIR bands. The routine generates five intermediate water masks, which are spatially intersected to create a single intermediate water mask. In order to remove very small waterbodies and any remaining gaps in the intermediate water mask, morphological opening and closing were performed to generate the final water mask. This proposed algorithm was used to extract water masks from some RapidEye images. It yielded an Overall Accuracy of 95% and a mean Kappa Statistic of 0.889 using the confusion matrix approach.

Pollution of Environmental Endocrine Disrupting Chemicals(EDCs) in Water and Its Adverse Reproductive Effect on Fish

Environmental endocrine disrupting chemicals （EDCs）, commonly found in the environment, come from industry and agriculture, including pesticides, fungicides, insecticides, herbicides, and other chemicals. Nowadays, more and more EDCs were released into the environment. EDCs go into water body via atmosphere sedi-mentation, surface runoff, soil eluviation, etc., so water body becomes the main place for existing. In order to attract scientific and public attention worldwide and to prevent EDCs pol ution, in this study we reviewed the classification of EDCs and their concentrations in natural water bodies, drinking water sources and water plants, and the reproductive toxicity of EDCs to fish were reviewed. EDCs could disturb the endocrine system and make reproductive organs and reproduction abnor-mal, resulting in fertility descending, reproduction function damage, community quan-tity decrease and even species extinction. In addition, EDCs could disrupt the homeostasis maintained by hormones, which would result in defects of neural de-velopment and abnormalities of the endocrine and reproductive systems. The exact molecular mechanisms have not been completely reported, but researches have suggested that multiple mechanisms were involved in the action of EDCs. Although there have been researches on the biohazard of EDCs, there stil exist problems of weakness in fundamental researches, difficulties in recognizing and identifying EDCs and high cost, which restraint the knowledge on them.

Bioturbation Effects of Benthic Fish on the Phosphorus Dynamic in Overlying Water of Paddy Field

[Objective]The research aimed to investigate the bioturbation effects of benthic fish Misgurnus anguillicaudatus on phosphorus dynamic in overlying water of paddy field,as well as to explore the bioturbation mechanism.[Method]Based on simulation experiment,the phosphorus contents in overlying water were analyzed comparatively with and without Misgurnus anguillicaudatus by the using of ion chromatography and spectrophotometry.[Result]The concentrations of total phosphorus(TP),dissolved total phosphorus(DTP)and particular phosphorus(PP)in bioturbation group had no significant differences with those in control group in initial stage of experiment,and became significantly higher than control group in middle and late stages of experiment(P<0.05). The PP/TP ratios in bioturbation group were bigger than those in control group,the increase of TP concentration in bioturbation group was mainly due to the increase of PP. The ratios of dissolved inorganic phosphorus(DIP) to DTP (DIP/DTP) were significantly bigger than those in control group in middle and late stages of experiment(P<0.05).[Conclusion]The benthic fish had bioturbation effects on phosphorus in overlying water of paddy field,which increased the available phosphorus for rice growth.

Response of Ficus microcarpa L.Foliage to Water Stress Determined by Chlorophyll Fluorescence Imaging Technique

[Objective] This study was to determine the response of Ficus microcarpa L. foliage to polyethylene glycol （PEG） simulated water stress using chlorophyll fluo- rescence imaging technique. [Method] The responses of detached leaves from Ficus microcarpa, Ficus benjamina and Nerium oleander to PEG-6000 simulated water stress were detected, and the chlorophyll fluorescence imaging technique was used to detect and analyze the stress at different spots of a single leaf simultaneously. [Result] The responses of Ficus microcarpa, Ficus benjamina and Nerium oleander to dehydration showed that： ~1~） the maximal photochemical efficiency （Fv/Fm） and non- photo-chemical quenching （NPQ） values were small in the reaction center among different detected spots of leaves, and there were great differences between relative electron transport rate （ETR）, photochemical quenching （qP） and quantum efficiency of PSII photochemistry （（φPSII）; （2） the differences of these parameters were more ob- vious among different spots of water-stressed leaves; （3） the discrete degrees of the species with strong resitances decreased significantly. [Conclusion] This study lays the foundation for the further research on the response of plants to drought stress using chlorophyll fluorescence imaging technique.

基于ImagePy的水敏纸图像预处理及液滴参数测量

快速获取喷施农药后雾滴在水敏纸表面的沉积分布,对了解农药的田间分布情况有十分重要的意义。针对目前水敏纸图像处理软件缺少对水敏纸图像的旋转等预处理操作,以及将水敏纸图像先转换为灰度图像再进行分割而导致检测精度低的问题,基于ImagePy开发了一种可以快速准确检测雾滴尺寸及分布特性的水敏纸图像处理软件,该软件由一组自定义插件组成,可以对水敏纸图像进行自动检测并旋转,然后对水敏纸图像进行彩色图像分割,进而使用这些插件统计测量雾滴尺寸、分布、总雾滴数和雾滴密度等雾滴参数,并将检测结果保存在Excel表格中以便后续数据处理,通过与DepositScan软件进行比较,验证了本软件的有效性。实验结果表明,基于ImagePy的水敏纸图像预处理及液滴参数测量方法可提取试纸上94.1176%以上的雾滴,较DepositScan软件准确率提升了6.7707%。