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Upsampling01:22

Upsampling

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Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
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When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
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    Area of Science:

    • Video processing and compression
    • Computer vision
    • Digital signal processing

    Background:

    • Frame rate up conversion (FRUC) enhances video quality but increases bitrate and can introduce artifacts.
    • High efficiency video coding (HEVC) aims to reduce bitrate for video transmission.
    • Integrating FRUC with HEVC presents challenges in maintaining quality and efficiency.

    Purpose of the Study:

    • To propose a novel framework integrating FRUC and HEVC based on rate-distortion optimization.
    • To enable reconstruction of interpolated frames at the encoder side with low bitrate cost and high visual quality.
    • To address the trade-off between bitrate consumption and visual quality in FRUC-enhanced HEVC.

    Main Methods:

    • Joint Motion Estimation (JME) algorithm to obtain shared robust motion vectors between FRUC and HEVC.
    • Embedding JME into the HEVC coding loop using its original motion search strategy.
    • Formulating frame interpolation as a rate-distortion optimization problem, considering bitrate and visual quality.
    • Establishing a distortion model for interpolated frames based on motion vector reliability and quantization error.

    Main Results:

    • The proposed framework successfully integrates FRUC with HEVC.
    • Achieved significant bitrate reduction compared to traditional cascaded methods.
    • Demonstrated 21% to 42% reduction in BDBR (Bjøntegaard Delta Rate) compared to traditional FRUC cascaded with coding.

    Conclusions:

    • The novel integration framework effectively reduces bitrate consumption for high frame rate videos generated by FRUC.
    • The proposed method achieves high visual quality for interpolated frames while minimizing coding bitrate cost.
    • This approach offers a superior solution for FRUC-HEVC integration compared to traditional cascaded methods.