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Related Concept Videos

Quality of Water01:19

Quality of Water

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In concrete preparation, the quality of water is paramount as it affects the strength and durability of the concrete. Potable water is usually preferred; however, it must not have excessive sodium or potassium to prevent compromising the concrete's integrity. Water quality is typically evaluated based on impurities such as dissolved solids, chlorides, and sulfates, and its pH value is ideally between 6 and 8. Even slightly acidic natural water may be acceptable unless it contains harmful...
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Testing Water Quality01:14

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When the quality of water for concrete preparation is uncertain, its impact on the setting time of cement and compressive strength of mortar is assessed by comparison with de-ionized or distilled water benchmarks. American Society for Testing and Materials (ASTM) C1602 requires the setting times to be within 90 minutes of the control, British Standard (BS) 3146:1980 allows a 30-minute variance in the initial setting, while British Standards European Norm (BS EN) 1008 specifies initial setting...
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Ultrasonography is an imaging technique that uses high-frequency sound waves to visualize the body's internal structures. It is a non-invasive and safe procedure that does not involve the use of ionizing radiation, making it widely used in various medical fields. Ultrasonography is used to study heart function, blood flow in the neck or extremities, certain conditions such as gallbladder disease, and fetal growth and development.
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Imaging Biological Samples with Optical Microscopy01:18

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Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
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Related Experiment Video

Updated: Sep 1, 2025

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
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Published on: April 18, 2025

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UIF: An Objective Quality Assessment for Underwater Image Enhancement.

Yannan Zheng, Weiling Chen, Rongfu Lin

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |August 11, 2022
    PubMed
    Summary

    A new Underwater Image Fidelity (UIF) metric objectively evaluates enhanced underwater images. This metric outperforms existing methods and addresses limitations of subjective and deep learning-based evaluations.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Oceanography

    Background:

    • Underwater imaging suffers from complex lighting, scattering, and noise, degrading visual quality.
    • Underwater Image Enhancement (UIE) techniques are crucial for improving visual fidelity.
    • Existing objective UIE evaluation methods struggle with deep learning approaches.

    Purpose of the Study:

    • To propose a novel objective metric, Underwater Image Fidelity (UIF), for evaluating enhanced underwater images.
    • To address the limitations of time-consuming subjective evaluations and inadequate objective metrics for modern UIE methods.

    Main Methods:

    • Developed the UIF metric by analyzing statistical features in CIELab color space.
    • Incorporated naturalness, sharpness, and structure indexes, combined via saliency-based spatial pooling.
    • Created the Underwater Image Enhancement Database (UIED) with subjective scores for validation.

    Main Results:

    • The proposed UIF metric demonstrates superior performance compared to existing underwater and general image quality metrics.
    • Experimental results validate the effectiveness of UIF in objectively assessing UIE performance.
    • The UIED database provides a benchmark for UIE research.

    Conclusions:

    • The UIF metric offers a reliable and efficient objective evaluation for enhanced underwater images.
    • The developed metric and database advance the field of underwater image processing and analysis.
    • UIF is particularly valuable for evaluating emerging deep learning-based UIE techniques.