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Fast bilateral filter with arbitrary range and domain kernels.

Bahadir K Gunturk

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |March 18, 2011
    PubMed
    Summary
    This summary is machine-generated.

    This paper introduces a faster bilateral filter using multiple optimized box kernels for better approximation. The method enhances image processing efficiency with minimal computational overhead.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Signal Processing

    Background:

    • The bilateral filter is a powerful edge-preserving smoothing filter used in image processing.
    • Fast approximations are crucial for real-time applications but often sacrifice accuracy.
    • Existing methods like the histogram-based approach use a single uniform box kernel for domain approximation.

    Discussion:

    • This work extends the histogram-based fast bilateral filter by employing multiple, optimally combined box kernels.
    • This strategy allows for a more accurate approximation of arbitrary domain kernels compared to using a single kernel.
    • The computational complexity increase is minimal, making it suitable for practical implementations.

    Key Insights:

    • A novel fast bilateral filter implementation achieving superior approximation accuracy for arbitrary kernels.
    • Optimal combination of multiple box kernels significantly improves upon single-kernel approximations.
    • Derivation of the optimal kernel size for single box kernel approximations is also presented.

    Outlook:

    • Potential for real-time high-fidelity image denoising and enhancement.
    • Further research could explore adaptive kernel selection for varying image content.
    • This approach could be extended to other filtering techniques requiring domain kernel approximation.