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Fast and Provably Accurate Bilateral Filtering.

Kunal N Chaudhury, Swapnil D Dabhade

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |April 20, 2016
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    Summary
    This summary is machine-generated.

    This study introduces a fast algorithm to approximate the bilateral filter, significantly reducing computational cost for edge-preserving image smoothing. The method achieves O(1) complexity per pixel, offering a competitive alternative to existing techniques.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Signal Processing

    Background:

    • The bilateral filter is crucial for edge-preserving image smoothing.
    • Direct computation is computationally expensive, scaling with filter support size (S).

    Purpose of the Study:

    • To develop a fast and accurate approximation algorithm for the bilateral filter.
    • To reduce computational complexity from O(S) to O(1) per pixel.

    Main Methods:

    • Developed a novel algorithm approximating the bilateral filter with a Gaussian range kernel.
    • The algorithm uses N+1 spatial filterings for approximation order N.
    • Analyzed filtering accuracy relative to the target bilateral filter.

    Main Results:

    • Achieved O(1) computational complexity per pixel for box and Gaussian spatial filters.
    • Demonstrated competitive speed and accuracy against state-of-the-art methods.
    • Provided a method to estimate the required approximation order (N) for desired accuracy.

    Conclusions:

    • The proposed algorithm offers a significant speedup for bilateral filtering.
    • It provides a provably accurate approximation with controllable accuracy via order N.
    • The method is practical and competitive for image processing applications.