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 new patents that has the capbility to change the future of water resource development

A complex web of extreme events, such as devastating floods in some areas and severe water scarcity in others, are increasingly characterizing the global water crisis. This situation is made worse by the sneaky contamination of water sources with "forever chemicals" that do not decompose in the environment. A complex issue necessitating immediate action to guarantee access to clean, safe water for all populations is created by this pollution and the considerable water loss that occurs during delivery to customers as a result of aging infrastructure. Climate change is causing an increase in extreme events like floods and droughts, leading to unpredictable water availability. Water scarcity is also increasing, especially in areas with high population density and agricultural demands. Persistent organic pollutants like PFAS are contaminating water supplies, posing health risks due to their non-biodegradability. Inefficient infrastructure and leaky pipes contribute to significant...
Read more

Five new ideas for starting a business in Hydro informatics

The popularity of AI, ML, and other data science technologies encouraged many aspiring entrepreneurs to launch businesses in these fields. Startups can prosper when combined with water and data science.  There are five new examples : Start-Up Idea 1 Portable Water Quality Indicating Meters Start-Up Idea 2 Reliability Indicator of Water Filters Start-Up Idea 3 Blue and Grey Water Monitoring Device Start-Up Idea 4 Remote Monitoring of Water Use Start-Up Idea 5 Virtual Water and Water Footprint Calculator The ideas are explained in detail at : https://hydrogeek.substack.com/ Thanking you, @Mrinmoy's Page @courses_hydrology , @Merchandise or @ @products_sustainability Add to Listy
Read more