Module filter

Functions for filtering images.

Structs

Kernel

A 2D kernel, used to filter images via convolution.

Functions

bilateral_filter

Denoise 8-bit grayscale image using bilateral filtering.

box_filter

Convolves an 8bpp grayscale image with a kernel of width (2 * x_radius + 1) and height (2 * y_radius + 1) whose entries are equal and sum to one. i.e. each output pixel is the unweighted mean of a rectangular region surrounding its corresponding input pixel. We handle locations where the kernel would extend past the image’s boundary by treating the image as if its boundary pixels were repeated indefinitely.

filter3x3

Returns 2d correlation of an image with a 3x3 row-major kernel. Intermediate calculations are performed at type K, and the results clamped to subpixel type S. Pads by continuity.

gaussian_blur_f32

Blurs an image using a Gaussian of standard deviation sigma. The kernel used has type f32 and all intermediate calculations are performed at this type.

horizontal_filter

Returns horizontal correlations between an image and a 1d kernel. Pads by continuity. Intermediate calculations are performed at type K.

median_filter

Applies a median filter of given dimensions to an image. Each output pixel is the median of the pixels in a (2 * x_radius + 1) * (2 * y_radius + 1) kernel of pixels in the input image.

separable_filter

Returns 2d correlation of view with the outer product of the 1d kernels h_kernel and v_kernel.

separable_filter_equal

Returns 2d correlation of an image with the outer product of the 1d kernel filter with itself.

sharpen3x3

Sharpens a grayscale image by applying a 3x3 approximation to the Laplacian.

sharpen_gaussian

Sharpens a grayscale image using a Gaussian as a low-pass filter.

vertical_filter

Returns horizontal correlations between an image and a 1d kernel. Pads by continuity.