{"id":22758759,"url":"https://github.com/aymen016/image-processing-algorithms","last_synced_at":"2026-04-13T18:02:12.429Z","repository":{"id":259449388,"uuid":"877909467","full_name":"Aymen016/Image-Processing-Algorithms","owner":"Aymen016","description":"Explore Python-based image processing from scratch with core algorithms like interpolation, convolution, and filtering!","archived":false,"fork":false,"pushed_at":"2024-11-05T16:12:54.000Z","size":1006,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-14T14:07:27.506Z","etag":null,"topics":["matplotlib","numpy","pillow","python"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/Aymen016.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}},"created_at":"2024-10-24T13:01:50.000Z","updated_at":"2024-12-04T16:15:00.000Z","dependencies_parsed_at":"2025-03-30T08:26:18.165Z","dependency_job_id":null,"html_url":"https://github.com/Aymen016/Image-Processing-Algorithms","commit_stats":null,"previous_names":["aymen016/image-processing-algorithms"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Aymen016/Image-Processing-Algorithms","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Aymen016%2FImage-Processing-Algorithms","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Aymen016%2FImage-Processing-Algorithms/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Aymen016%2FImage-Processing-Algorithms/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Aymen016%2FImage-Processing-Algorithms/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Aymen016","download_url":"https://codeload.github.com/Aymen016/Image-Processing-Algorithms/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Aymen016%2FImage-Processing-Algorithms/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31764317,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-13T15:25:13.801Z","status":"ssl_error","status_checked_at":"2026-04-13T15:25:09.162Z","response_time":93,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["matplotlib","numpy","pillow","python"],"created_at":"2024-12-11T08:15:42.355Z","updated_at":"2026-04-13T18:02:12.414Z","avatar_url":"https://github.com/Aymen016.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Image-Processing-Algorithms\n\nThis repository contains Python implementations of basic image processing algorithms developed from scratch without using any external image processing libraries.\n\n## Overview\n\nThe following algorithms are implemented:\n1. **Nearest Neighbor Interpolation and Resizing** - Resize an image using Nearest Neighbor Interpolation.\n2. **Bilinear Interpolation and Resizing** - Resize an image using Bilinear Interpolation.\n3. **Convolution** - Apply a convolution operation to an input image with a specified kernel.\n4. **Gaussian Filter** - Smooth an input image using a Gaussian filter.\n\n## Algorithms Description\n\n### 1. Nearest Neighbor Interpolation\nThe simplest interpolation technique that selects the closest pixel value to assign to the new pixel in the resized image. It’s fast but results in blocky images.\n\n![Screenshot 2024-11-05 210144](https://github.com/user-attachments/assets/458c0f18-bd18-4f5d-94e9-e86ae12f2fa8)\n\n### 2. Bilinear Interpolation\nThis technique considers a weighted average of the four nearest pixel values to compute the new pixel value. It produces smoother results compared to nearest neighbor interpolation.\n\n![Screenshot 2024-11-05 211045](https://github.com/user-attachments/assets/c1e7e3dc-d3b7-4201-af58-8c965eb7b689)\n\n### 3. Convolution\nConvolution is an operation that slides a small matrix called a kernel across an image and computes the weighted sum of the overlapping pixel values to produce a filtered image. This is commonly used for feature extraction.\n\n![Screenshot 2024-11-05 211135](https://github.com/user-attachments/assets/9d4010c4-839e-418c-a530-d738f4dca8da)\n\n### 4. Gaussian Filter\nThe Gaussian filter is used for image smoothing by reducing noise and detail. It applies a Gaussian function over the image and uses convolution to blur the image.\n\n![Screenshot 2024-11-05 211201](https://github.com/user-attachments/assets/f39c63d3-8193-45ca-a7cf-0668716e1022)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faymen016%2Fimage-processing-algorithms","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faymen016%2Fimage-processing-algorithms","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faymen016%2Fimage-processing-algorithms/lists"}