Unsupervised Multi-Expert Learning Model for Underwater Image Enhancement

Underwater image enhancement aims to restore a clean appearance and thus improves the quality of underwater degraded images.Current methods feed the whole image directly into the model for enhancement.However,they ignored that the R,G and B channels of underwater degraded images present varied degrees of degradation,due to the selective absorption for the light.To address this issue,we propose an unsupervised multi-expert learning model by considering the enhancement of each color channel.Specifically,an unsupervised architecture based on generative adversarial network is employed to alleviate the need for paired underwater images.Based on this,we design a generator,including a multi-expert encoder,a feature fusion module and a feature fusion-guided decoder,to generate the clear underwater image.Accordingly,a multi-expert discriminator is proposed to verify the authenticity of the R,G and B channels,respectively.In addition,content perceptual loss and edge loss are introduced into the loss function to further improve the content and details of the enhanced images.Extensive experiments on public datasets demonstrate that our method achieves more pleasing results in vision quality.Various metrics(PSNR,SSIM,UIQM and UCIQE) evaluated on our enhanced images have been improved obviously.

Assessment Framework of Green Intelligent Transformation of Small Hydropower in China

With the comprehensive promoted construction of the establishment of green small hydropower,the defects of existing small hydropower station are gradually emerging,and it is necessary to implement green intelligent transformation to promote the construction of energy internet in China.This study focuses on constructing a green intelligent planning and transforming assessment framework,and assists management department to filtrate the small hydropower stations which can be transformed reasonably.Firstly,power station economy,ecological environment,technical safety management and social benefits are involved in the assessment index system.Secondly,multi-expert judgment aggregation based on fuzzed comparison scale is put forward to calculate the index value,and evidence synthesis is used to comprehensively assess the feasibility of green and intelligent planning and transformation for several small hydropower stations.The simulation case analysis shows the constructed assessment framework can reflect the actual situation of objectives properly and would provide decision-making basis for green and intelligent planning and transformation of small hydropower stations.