UnsharpMask

Description

Sharpen the input image using Unsharp Masking processing and overlays the result with the original image.

    Args:
        blur_limit: maximum Gaussian kernel size for blurring the input image.
            Must be zero or odd and in range [0, inf). If set to 0 it will be computed from sigma
            as `round(sigma * (3 if img.dtype == np.uint8 else 4) * 2 + 1) + 1`.
            If set single value `blur_limit` will be in range (0, blur_limit).
            Default: (3, 7).
        sigma_limit: Gaussian kernel standard deviation. Must be in range [0, inf).
            If set single value `sigma_limit` will be in range (0, sigma_limit).
            If set to 0 sigma will be computed as `sigma = 0.3*((ksize-1)*0.5 - 1) + 0.8`. Default: 0.
        alpha: range to choose the visibility of the sharpened image.
            At 0, only the original image is visible, at 1.0 only its sharpened version is visible.
            Default: (0.2, 0.5).
        threshold: Value to limit sharpening only for areas with high pixel difference between original image
            and it's smoothed version. Higher threshold means less sharpening on flat areas.
            Must be in range [0, 255]. Default: 10.
        p: probability of applying the transform. Default: 0.5.

    Reference:
        arxiv.org/pdf/2107.10833.pdf

    Targets:
        image

    

Parameters

• p: float (default: 0.5)
• sigma_limit: int | tuple[int, int] | float | tuple[float, float] (default: 0)
• alpha: int | tuple[int, int] | float | tuple[float, float] (default: (0.2, 0.5))
• threshold: int (default: 10)
• blur_limit: int | tuple[int, int] (default: (3, 7))

Targets

• Image

Try it out