image/imageops/
fast_blur.rs

Help
1use num_traits::clamp;
2
3use crate::{ImageBuffer, Pixel, Primitive};
4
5/// Approximation of Gaussian blur after
6/// Kovesi, P.:  Fast Almost-Gaussian Filtering The Australian Pattern
7/// Recognition Society Conference: DICTA 2010. December 2010. Sydney.
8/// This method assumes alpha pre-multiplication for images that contain non-constant alpha.
9#[must_use]
10pub fn fast_blur<P: Pixel>(
11    image_buffer: &ImageBuffer<P, Vec<P::Subpixel>>,
12    sigma: f32,
13) -> ImageBuffer<P, Vec<P::Subpixel>> {
14    let (width, height) = image_buffer.dimensions();
15
16    if width == 0 || height == 0 {
17        return image_buffer.clone();
18    }
19    let mut samples = image_buffer.as_flat_samples().samples.to_vec();
20    let num_passes = 3;
21
22    let boxes = boxes_for_gauss(sigma, num_passes);
23
24    for radius in boxes.iter().take(num_passes) {
25        let horizontally_blurred_transposed = horizontal_fast_blur_half::<P::Subpixel>(
26            &samples,
27            width as usize,
28            height as usize,
29            (*radius - 1) / 2,
30            P::CHANNEL_COUNT as usize,
31        );
32        samples = horizontal_fast_blur_half::<P::Subpixel>(
33            &horizontally_blurred_transposed,
34            height as usize,
35            width as usize,
36            (*radius - 1) / 2,
37            P::CHANNEL_COUNT as usize,
38        );
39    }
40    ImageBuffer::from_raw(width, height, samples).unwrap()
41}
42
43fn boxes_for_gauss(sigma: f32, n: usize) -> Vec<usize> {
44    let w_ideal = f32::sqrt((12.0 * sigma.powi(2) / (n as f32)) + 1.0);
45    let mut w_l = w_ideal.floor();
46    if w_l % 2.0 == 0.0 {
47        w_l -= 1.0;
48    };
49    let w_u = w_l + 2.0;
50
51    let m_ideal = 0.25 * (n as f32) * (w_l + 3.0) - 3.0 * sigma.powi(2) * (w_l + 1.0).recip();
52
53    let m = f32::round(m_ideal) as usize;
54
55    (0..n)
56        .map(|i| if i < m { w_l as usize } else { w_u as usize })
57        .collect::<Vec<_>>()
58}
59
60fn channel_idx(channel: usize, idx: usize, channel_num: usize) -> usize {
61    channel_num * idx + channel
62}
63
64fn horizontal_fast_blur_half<P: Primitive>(
65    samples: &[P],
66    width: usize,
67    height: usize,
68    r: usize,
69    channel_num: usize,
70) -> Vec<P> {
71    let channel_size = width * height;
72
73    let mut out_samples = vec![P::from(0).unwrap(); channel_size * channel_num];
74    let mut vals = vec![0.0; channel_num];
75
76    let min_value = P::DEFAULT_MIN_VALUE.to_f32().unwrap();
77    let max_value = P::DEFAULT_MAX_VALUE.to_f32().unwrap();
78
79    for row in 0..height {
80        for (channel, value) in vals.iter_mut().enumerate().take(channel_num) {
81            *value = ((-(r as isize))..(r + 1) as isize)
82                .map(|x| {
83                    extended_f(
84                        samples,
85                        width,
86                        height,
87                        x,
88                        row as isize,
89                        channel,
90                        channel_num,
91                    )
92                    .to_f32()
93                    .unwrap_or(0.0)
94                })
95                .sum();
96        }
97
98        for column in 0..width {
99            for (channel, channel_val) in vals.iter_mut().enumerate() {
100                let val = *channel_val / (2.0 * r as f32 + 1.0);
101                let val = clamp(val, min_value, max_value);
102                let val = P::from(val).unwrap();
103
104                let destination_row = column;
105                let destination_column = row;
106                let destination_sample_index = channel_idx(
107                    channel,
108                    destination_column + destination_row * height,
109                    channel_num,
110                );
111                out_samples[destination_sample_index] = val;
112                *channel_val = *channel_val
113                    - extended_f(
114                        samples,
115                        width,
116                        height,
117                        column as isize - r as isize,
118                        row as isize,
119                        channel,
120                        channel_num,
121                    )
122                    .to_f32()
123                    .unwrap_or(0.0)
124                    + extended_f(
125                        samples,
126                        width,
127                        height,
128                        { column + r + 1 } as isize,
129                        row as isize,
130                        channel,
131                        channel_num,
132                    )
133                    .to_f32()
134                    .unwrap_or(0.0);
135            }
136        }
137    }
138
139    out_samples
140}
141
142fn extended_f<P: Primitive>(
143    samples: &[P],
144    width: usize,
145    height: usize,
146    x: isize,
147    y: isize,
148    channel: usize,
149    channel_num: usize,
150) -> P {
151    let x = clamp(x, 0, width as isize - 1) as usize;
152    let y = clamp(y, 0, height as isize - 1) as usize;
153    samples[channel_idx(channel, y * width + x, channel_num)]
154}
image/imageops/fast_blur.rs

image/imageops/
fast_blur.rs
