Struct ConvolutionKernel 

pub struct ConvolutionKernel {
    pub size: u32,
    pub values: Vec<f32>,
    pub divisor: f32,
    pub bias: f32,
    pub preserve_alpha: bool,
}

Convolution kernel for custom filtering operations.

Defines a square matrix of weights used for convolution-based image processing. The kernel is applied to each pixel by multiplying surrounding pixels by the weights, summing the results, dividing by the divisor, and adding the bias.

Fields

size: u32

Kernel size (e.g., 3 for a 3×3 kernel, 5 for 5×5). The kernel must be square, so this defines both width and height.

values: Vec<f32>

Kernel weight values in row-major order. Length must equal size × size. Center of kernel is typically at (size/2, size/2).

divisor: f32

Normalization divisor applied to the convolution result. Common practice is to use the sum of all weights for averaging, or 1.0 otherwise.

bias: f32

Bias value added to the result after normalization. Useful for edge detection or emboss effects to shift the result range.

preserve_alpha: bool

Whether to preserve the alpha channel unchanged. If true, convolution only applies to RGB; if false, it applies to RGBA.

Trait Implementations

impl Clone for ConvolutionKernel

fn clone(&self) -> ConvolutionKernel

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for ConvolutionKernel

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq for ConvolutionKernel

fn eq(&self, other: &ConvolutionKernel) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for ConvolutionKernel