Crates.io | image-dwt |
lib.rs | image-dwt |
version | 0.4.1 |
source | src |
created_at | 2024-03-20 14:23:10.335503 |
updated_at | 2024-05-03 02:28:45.846673 |
description | An implementation of the À Trous Discrete Wavelet Transform for images |
homepage | https://github.com/anshap1719/image-dwt |
repository | https://github.com/anshap1719/image-dwt |
max_upload_size | |
id | 1180540 |
size | 47,898 |
This project provides an implementation of the À Trous Discrete Wavelet Transform (DWT) algorithm for images. The À Trous DWT is a technique used for signal and image processing, particularly for tasks such as denoising, compression, and feature extraction.
The À Trous DWT is a variation of the Discrete Wavelet Transform (DWT) that involves convolution with a filter bank. It decomposes an image into different frequency sub-bands, allowing for analysis at multiple resolutions. This implementation supports both forward and inverse transforms.
I'm trying to build a suite of tools in rust that facilitate image processing, primarily deep sky images and data. Wavelet transform and multi-resolution analysis is a very widely used transform in these cases.
fn remove_large_scale_structures() {
let image = image::open("./sample.jpg").unwrap();
let transform = ATrousTransform::new(&image, 6, B3SplineKernel);
let recomposed = transform
.into_iter()
// Skip pixel scale 0 layer for noise removal
.skip(1)
// Only take layers where pixel scale is less than 2
.filter(|item| item.pixel_scale.is_some_and(|scale| scale < 2))
// Recompose processed layers into final image
.recompose_into_image(image.width() as usize, image.height() as usize);
recomposed.to_rgb8().save("recombined.jpg").unwrap()
}
To use this library in your Rust project, add the following to your Cargo.toml
file:
[dependencies]
image_dwt = "0.3.2"