{"id":19073228,"url":"https://github.com/anshap1719/image-dwt","last_synced_at":"2025-04-28T18:56:15.040Z","repository":{"id":228396428,"uuid":"773868098","full_name":"anshap1719/image-dwt","owner":"anshap1719","description":"An implementation of the À Trous Discreet Wavelet Transform For Images Based On image-rs Crate","archived":false,"fork":false,"pushed_at":"2024-09-15T13:06:57.000Z","size":102,"stargazers_count":6,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-28T18:56:09.933Z","etag":null,"topics":["astronomical-algorithms","astronomy","image-processing","rust","wavelet-transform"],"latest_commit_sha":null,"homepage":"","language":"Rust","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/anshap1719.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2024-03-18T14:39:33.000Z","updated_at":"2025-01-10T17:52:29.000Z","dependencies_parsed_at":"2024-03-26T12:31:29.500Z","dependency_job_id":"90721cd1-8e10-4124-9ac7-d4d762f1410c","html_url":"https://github.com/anshap1719/image-dwt","commit_stats":null,"previous_names":["anshap1719/image-dwt"],"tags_count":8,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anshap1719%2Fimage-dwt","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anshap1719%2Fimage-dwt/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anshap1719%2Fimage-dwt/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anshap1719%2Fimage-dwt/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/anshap1719","download_url":"https://codeload.github.com/anshap1719/image-dwt/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251372466,"owners_count":21578964,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["astronomical-algorithms","astronomy","image-processing","rust","wavelet-transform"],"created_at":"2024-11-09T01:46:00.129Z","updated_at":"2025-04-28T18:56:15.024Z","avatar_url":"https://github.com/anshap1719.png","language":"Rust","funding_links":[],"categories":[],"sub_categories":[],"readme":"# À Trous Discrete Wavelet Transform (DWT) for image-rs\n\nThis project provides an implementation of the À Trous Discrete Wavelet Transform (DWT) algorithm for images. The À\nTrous DWT is a technique used for signal and image processing, particularly for tasks such as denoising, compression,\nand feature extraction.\n\n## Overview\n\nThe À Trous DWT is a variation of the Discrete Wavelet Transform (DWT) that involves convolution with a filter bank. It\ndecomposes an image into different frequency sub-bands, allowing for analysis at multiple resolutions. This\nimplementation supports both forward and inverse transforms.\n\n## Why\n\nI'm trying to build a suite of tools in rust that facilitate image processing, primarily deep sky images and data.\nWavelet transform and multi-resolution analysis is a very widely used transform in these cases.\n\n## Usage\n\n```rust\nfn remove_large_scale_structures() {\n    let image = image::open(\"./sample.jpg\").unwrap();\n    let transform = ATrousTransform::new(\u0026image, 6, B3SplineKernel);\n\n    let recomposed = transform\n        .into_iter()\n        // Skip pixel scale 0 layer for noise removal\n        .skip(1)\n        // Only take layers where pixel scale is less than 2\n        .filter(|item| item.pixel_scale.is_some_and(|scale| scale \u003c 2))\n        // Recompose processed layers into final image\n        .recompose_into_image(image.width() as usize, image.height() as usize);\n\n    recomposed.to_rgb8().save(\"recombined.jpg\").unwrap()\n}\n```\n\n## Installation\n\nTo use this library in your Rust project, add the following to your `Cargo.toml` file:\n\n```toml\n[dependencies]\nimage_dwt = \"0.3.2\"","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanshap1719%2Fimage-dwt","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fanshap1719%2Fimage-dwt","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanshap1719%2Fimage-dwt/lists"}