{"id":16106055,"url":"https://github.com/gfacciol/dctdenoising","last_synced_at":"2025-03-18T08:31:57.960Z","repository":{"id":73423618,"uuid":"46111028","full_name":"gfacciol/DCTdenoising","owner":"gfacciol","description":null,"archived":false,"fork":false,"pushed_at":"2022-11-04T11:51:22.000Z","size":3921,"stargazers_count":16,"open_issues_count":0,"forks_count":9,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-03-16T18:21:28.268Z","etag":null,"topics":["algorithm","image-denoising","image-processing","ipol"],"latest_commit_sha":null,"homepage":null,"language":"C","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/gfacciol.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG","contributing":null,"funding":null,"license":"LICENSE","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":"2015-11-13T08:55:45.000Z","updated_at":"2025-03-08T14:12:14.000Z","dependencies_parsed_at":null,"dependency_job_id":"9f100f0c-a0ad-4f10-988f-09c694aaf658","html_url":"https://github.com/gfacciol/DCTdenoising","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gfacciol%2FDCTdenoising","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gfacciol%2FDCTdenoising/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gfacciol%2FDCTdenoising/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gfacciol%2FDCTdenoising/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/gfacciol","download_url":"https://codeload.github.com/gfacciol/DCTdenoising/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244184202,"owners_count":20412170,"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":["algorithm","image-denoising","image-processing","ipol"],"created_at":"2024-10-09T19:11:48.814Z","updated_at":"2025-03-18T08:31:57.954Z","avatar_url":"https://github.com/gfacciol.png","language":"C","funding_links":[],"categories":[],"sub_categories":[],"readme":"% Multiscale DCT image denoising.\n\n# ABOUT\n\n* Author : Nicola Pierazzo   \u003cnicolapierazzo@gmail.com\u003e\n* Author : Gabriele Facciolo \u003cgfacciol@gmail.com\u003e\n* Copyright : (C) 2017 IPOL Image Processing On Line http://www.ipol.im/\n* Licence   : GPL v3+, see GPLv3.txt\n* Based on the 2010 implementation of DCT denoising by:\n  Guoshen Yu \u003cyu@cmap.polytechnique.fr\u003e and Guillermo Sapiro \u003cguille@umn.edu\u003e\n* Latest version available at: https://github.com/gfacciol/DCTdenoising\n\n# OVERVIEW\n\nThis source code provides an implementation of the \"Multiscale DCT denoising\"\nalgorithm described in the IPOL article: http://www.ipol.im/pub/art/2017/201\n\n# UNIX/LINUX/MAC USER GUIDE\n\nThe code is compilable on Unix/Linux and Mac OS. \n\n- Compilation. \nAutomated compilation requires the Cmake and make.\n\n- Dependencies.\nThis code requires the libpng, libtiff, libjpeg, and libfftw.\n\n- Image formats. \nOnly the PNG, JPEG, and TIFF (float) formats are supported. \n \n-------------------------------------------------------------------------\nUsage:\n1. Download the code package and extract it. Go to that directory. \n\n2. Compile the source code (on Unix/Linux/Mac OS). \n\n    mkdir build; cd build;\n    cmake ..; make;\n\n3. Runing DCT image denoising: parameters\n \n    ./dctdenoising sigma [input [output]]   # noise std, noisy image, output  \n       [-w patch_size (default 8)]   # DCT denoising patch size  \n       [-1 | -2 guide]               # -1: only hard thresh., -2: provide guide  \n       [-no_adaptive_aggregation]    # disable adaptive aggregation weights  \n       [-n scales(4)]                # multiscale: number of scales  \n       [-c factor(.5)]               # multiscale: recomposition factor  \n       [-single output_singlescale]  # multiscale: save also one-scale result  \n\n\nThe flag -1 permits to run DCT denoising only with the hard thresholding step,\nwhile -2 allows to specify the guide for the wiener filtering step.\nWhen not set both steps are executed using the output of the first one as guide\nfor the second one.\nSetting no_adaptive_aggregation disables the aggregation weights.\n\n\nExample, run\n\n    ./dctdenoising 15 ../noisy.tiff denoised.png\n\n\nTo visualize tiff (float) images use PVFLIP (https://github.com/gfacciol/pvflip) \nor ImageJ (https://imagej.nih.gov/ij/index.html)\n\n\n# ABOUT THIS FILE\nCopying and distribution of this file, with or without modification,\nare permitted in any medium without royalty provided the copyright\nnotice and this notice are preserved.  This file is offered as-is,\nwithout any warranty.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgfacciol%2Fdctdenoising","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgfacciol%2Fdctdenoising","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgfacciol%2Fdctdenoising/lists"}