Skip to main content

Underwater Image Processing 18of20



For more details: https://open.substack.com/pub/veryshorttermcourse/p/internship-3-underwater-image-processing?r=c8bxy&utm_campaign=post&utm_medium=web
"Submarine underwater image processing" leverages advanced techniques like AI and deep learning to enhance the quality of images captured by underwater drones and submarines, enabling detailed analysis of the ocean floor through "AI-assisted underwater mapping." This technology utilizes "deep learning for ocean floor analysis," allowing for automated identification of marine life, geological features, and potential hazards. By applying "underwater drone image enhancement" algorithms, researchers can overcome the inherent challenges of underwater imaging, including low visibility and color distortion, leading to improved "underwater image quality improvement with AI." 

This has significant implications for both scientific research, with applications in marine biology and environmental monitoring, and defense operations, where "real-time underwater image processing for defense" is crucial for surveillance and navigation. However, "challenges of underwater image processing" like light scattering and turbidity must be addressed to achieve optimal results in diverse underwater environments.

Key points:
  • Image enhancement:
    AI algorithms are used to improve the clarity and color accuracy of underwater images captured by submarines and drones.
  • Ocean floor mapping:
    Deep learning models can analyze underwater imagery to create detailed maps of the seabed, identifying geological features and potential hazards.
  • Scientific applications:
    Researchers can study marine life, monitor coral reef health, and assess environmental changes with enhanced underwater imagery.
  • Defense applications:
    Real-time image processing allows for underwater surveillance and navigation in challenging environments.
  • Technical challenges:
    Addressing issues like light attenuation, backscatter, and turbidity is crucial for accurate underwater image analysis.
Labels:

Popular posts from this blog

Five open source free hydrologic models that you can use to model runoff of micro to macro watersheds

The principal objective of hydrologic models is to forecast the runoff of a surface water body, especially dendritic systems like rivers, streams, etc. The inputs to these models are generally Rainfall/Precipitation, Soil Characteristics, and other Climatic parameters like evapotranspiration, humidity, etc. LULC and geo-morphology are also used as the required input parameters of the hydrologic models. Both input and output of these models are temporally as well as spatially variable. Now the resolution varies with different models. Some models consider all the sub-basins to be a single watershed and determine the output based on the characteristics of this single watershed(lumped).In contrast, some other models will consider the {impact|effect} of each of the sub-basins on the central outflow of the watershed(distributed).In a few models, the entire watershed is divided into grids or units of uniform dimension. However, the accuracy is highest for the models, which considers the {impa...
Read more

Five project ideas for "Hydroinformatics in Groundwater"

     In recent years, advanced soft computation techniques such as Multi-Criteria Decision Making and Geographical Information Systems have been widely used to solve water resource development problems. Hydroinformatics (Hydro means Hydrus or water, and informatics means information science) is a branch of science concerned with the application of advanced soft computation techniques and information and communication technologies (ICTs) to water-related problems. The following are five hydro informatics project topics that can be applied to groundwater problems. Complete Article at  HydroGeek Thanks, @Mrinmoy's Page @data_hydrology , @Merchandise or @ @products_sustainability Add to Listy /
Read more

5 Most Sustainable Decision Making Techniques Used In Water Resources Management

This video depicts the application of MCDM and Optimization Techniques in Water Resource Management Problems. A total of five studies were discussed which have the maximum citation among the papers published under the topic of Water Resource Management.  The video also provides the links to the tutorials of five Multi-Attribute Decision-Making techniques and five Multi-Objective Decision-Making methods which are mostly used in solving decision-making problems in sustainable water management objectives. Thanking you, Dr.Mrinmoy Majumder Subscribe to Hydrogeek Enroll in the MCDM course
Read more