def weighted_median_filter(a_img: ImageImpl, kernel_size: int) -> ImageImpl:
"""
Given an Image instance, apply the weighted median filter using a square kernel of size
kernel_size.
:param a_img: Image instance
:param kernel_size: kernel size int
:return: transformed image
"""
a_img.convolution(
kernel_size,
lambda window: _weighted_median(window, kernel_size),
)
return a_img
def high_filter(a_img: ImageImpl, kernel_size: int) -> ImageImpl:
"""
Given a Image instance, apply high value filter.
:param a_img:
:param kernel_size:
:return: transformed Image instance
"""
a_img.convolution(
kernel_size,
lambda window: apply_high_filter(window, int(kernel_size)),
)
return a_img
def gaussian_filter(a_img: ImageImpl, kernel_size: int, sigma: float) -> ImageImpl:
"""
Given an Image instance, apply the weighted gaussian filter using a square kernel of size
kernel_size.
:param a_img: Image instance
:param kernel_size: kernel size int
:param sigma: sigma value
:return: transformed image
"""
a_img.convolution(
kernel_size,
lambda window: _apply_gaussian_filter(window, int(kernel_size), sigma),
)
return a_img
def median_filter(a_img: ImageImpl, kernel_size: int) -> ImageImpl:
"""
Given an Image instance, apply the median filter using a square kernel of size
kernel_size.
:param a_img: Image instance
:param kernel_size: kernel size int
:return: transformed image
"""
a_img.convolution(
kernel_size,
lambda window: np.median(
window.reshape(
-1,
)
),
)
return a_img
