{
    "extrinsic": {
        "provider": "https://deposit.softwareheritage.org/1/private/1280/meta/",
        "raw": {
            "origin": {
                "type": "deposit",
                "url": "https://doi.org/10.5201/ipol.2016.161"
            },
            "origin_metadata": {
                "metadata": {
                    "atom:external_identifier": "ipol.2016.161",
                    "atom:title": "ipol_161",
                    "codemeta:applicationCategory": "Image Processing",
                    "codemeta:author": [
                        {
                            "codemeta:affiliation": "MAP5, Universit\u00e9 Paris Descartes, France",
                            "codemeta:name": "Julie Delon"
                        },
                        {
                            "codemeta:affiliation": "CNRS, CMLA, ENS Cachan, France",
                            "codemeta:name": "Agn\u00e8s Desolneux"
                        },
                        {
                            "codemeta:affiliation": "MAP5, Universit\u00e9 Paris Descartes, France",
                            "codemeta:name": "Thierry Guillemot"
                        }
                    ],
                    "codemeta:dateCreated": "2016-01-14",
                    "codemeta:datePublished": "2016-06-29",
                    "codemeta:description": "PARIGI: a Patch-based Approach to Remove Impulse-Gaussian Noise from Images",
                    "codemeta:downloadUrl": "http://www.ipol.im/pub/art/2016/161/parigi_1.2.zip",
                    "codemeta:identifier": "https://doi.org/10.5201/ipol.2016.161",
                    "codemeta:isPartOf": {
                        "codemeta:identifier": "ISSN: 2105-1232 DOI: 10.5201/ipol",
                        "codemeta:name": "Image Processing On Line (IPOL)",
                        "codemeta:type": "Journal"
                    },
                    "codemeta:keywords": [
                        "impulse noise",
                        "Gaussian noise",
                        "denoising",
                        "image patches"
                    ],
                    "codemeta:license": {
                        "codemeta:name": "GPL-3.0-or-later",
                        "codemeta:url": "https://spdx.org/licenses/GPL-3.0-or-later.html"
                    },
                    "codemeta:operatingSystem": "Linux",
                    "codemeta:programmingLanguage": "C",
                    "codemeta:referencePublication": {
                        "codemeta:abstract": "In this paper, we present an implementation of the PARIGI method that addresses the problem of the restoration of images affected by impulse noise or by a mixture of Gaussian and impulse noise. The method relies on a patch-based approach, which requires careful choices for both the distance between patches and for the statistical estimator of the original patch. Experiments are performed in the case of pure impulse noise and in the case of a mixture of Gaussian and impulse noise.",
                        "codemeta:identifier": "https://doi.org/10.5201/ipol.2016.161",
                        "codemeta:name": "PARIGI: a Patch-based Approach to Remove Impulse-Gaussian Noise from Images",
                        "codemeta:url": "http://www.ipol.im/pub/art/2016/161/article.pdf"
                    },
                    "codemeta:relatedLink": "http://demo.ipol.im/demo/161",
                    "codemeta:releaseNotes": "This code implements the algorithm(s) published in the IPOL paper \"PARIGI: a Patch-based Approach to Remove Impulse-Gaussian Noise from Images\"",
                    "codemeta:url": "http://www.ipol.im/pub/art/2016/161/",
                    "codemeta:version": "1.0"
                },
                "provider": {
                    "metadata": {},
                    "provider_name": "",
                    "provider_type": "deposit_client",
                    "provider_url": "https://doi.org/10.5201/"
                },
                "tool": {
                    "configuration": {
                        "sword_version": "2"
                    },
                    "name": "swh-deposit",
                    "version": "0.8.0"
                }
            }
        },
        "when": "2020-12-20T12:55:10.160583+00:00"
    },
    "original_artifact": [
        {
            "checksums": {
                "sha1": "241303e9c811ceac1981efd9684f536c3a7e8dc1",
                "sha256": "66f7e7a31e8ea152de3f101d3ed03c8bfe6418055c95dbd3e66bcb5ef50b67e5"
            },
            "filename": "archive.zip",
            "length": 224181,
            "url": "https://deposit.softwareheritage.org/1/private/1280/raw/"
        }
    ]
}