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Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
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To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
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Optical-Flow Based Nonlinear Weighted Prediction for SDR and Backward Compatible HDR Video Coding.

David Gommelet, Julien Le Tanou, Aline Roumy

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |October 16, 2019
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces new Weighted Prediction (WP) methods for High Efficiency Video Coding (HEVC) Standard Dynamic Range (SDR) compression. These methods enhance coding efficiency and temporal consistency, outperforming existing Tone Mapping Operators (TMOs).

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    Area of Science:

    • Video compression
    • Image processing
    • Computer vision

    Background:

    • Tone Mapping Operators (TMOs) for video are typically optimized for temporal consistency or coding efficiency.
    • Optimizing solely for coding efficiency can alter artistic intent, while temporal filtering doesn't improve SDR coding performance.

    Purpose of the Study:

    • To combine the benefits of temporal consistency and coding efficiency in video compression.
    • To introduce and evaluate novel Weighted Prediction (WP) methods within the HEVC SDR codec.

    Main Methods:

    • Developed new Weighted Prediction (WP) algorithms and modes for the HEVC SDR codec.
    • Implemented global motion compensation using optical flow and non-linear functions for new WP modes.
    • Evaluated methods for both HDR backward compatible and SDR-only compression scenarios.

    Main Results:

    • Demonstrated the effectiveness of WP methods over TMOs optimized solely for Rate Distortion (RD) performance.
    • Achieved improved RD performance in SDR compression.
    • Maintained SDR temporal coherence while enhancing compression efficiency.

    Conclusions:

    • The proposed WP methods offer a superior approach to video compression by balancing temporal consistency and RD optimization.
    • These novel methods provide significant improvements for both HDR backward compatible and SDR-only compression use cases.