{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:XDUHGJV3SW2UZN4ZTYITYE45BW","short_pith_number":"pith:XDUHGJV3","schema_version":"1.0","canonical_sha256":"b8e87326bb95b54cb7999e113c139d0d8d515d0e089e5a5174c752cea9a6b570","source":{"kind":"arxiv","id":"1611.08817","version":3},"attestation_state":"computed","paper":{"title":"A General Truncated Regularization Framework for Contrast-Preserving Variational Signal and Image Restoration: Motivation and Implementation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.NA","authors_text":"Chunlin Wu, Shuang Wen, Zhifang Liu","submitted_at":"2016-11-27T10:01:53Z","abstract_excerpt":"Variational methods have become an important kind of methods in signal and image restoration - a typical inverse problem. One important minimization model consists of the squared $\\ell_2$ data fidelity (corresponding to Gaussian noise) and a regularization term constructed by a potential function composed of first order difference operators. It is well known that total variation (TV) regularization, although achieved great successes, suffers from a contrast reduction effect. Using a typical signal, we show that, actually all convex regularizers and most nonconvex regularizers have this effect."},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1611.08817","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2016-11-27T10:01:53Z","cross_cats_sorted":[],"title_canon_sha256":"72ced19750baf91b48ced70f8e59a0b4ca0acaed1bd8207f62fb9f5bb711d970","abstract_canon_sha256":"ef6f539e6a6ac01f59c5cc3d4a052f9c0e4bb27c1d1b3de7a86cf7b2e4392804"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:13:19.736188Z","signature_b64":"wn1DwXUU4r4NwU2iYZWO0Hxsw6tdt+2gurHggtSsjzHQhdY4ztlnqrUuV1xwJlXCLIgiVQx7l5by5D3gD7/vAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b8e87326bb95b54cb7999e113c139d0d8d515d0e089e5a5174c752cea9a6b570","last_reissued_at":"2026-05-18T00:13:19.735668Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:13:19.735668Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A General Truncated Regularization Framework for Contrast-Preserving Variational Signal and Image Restoration: Motivation and Implementation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.NA","authors_text":"Chunlin Wu, Shuang Wen, Zhifang Liu","submitted_at":"2016-11-27T10:01:53Z","abstract_excerpt":"Variational methods have become an important kind of methods in signal and image restoration - a typical inverse problem. One important minimization model consists of the squared $\\ell_2$ data fidelity (corresponding to Gaussian noise) and a regularization term constructed by a potential function composed of first order difference operators. It is well known that total variation (TV) regularization, although achieved great successes, suffers from a contrast reduction effect. Using a typical signal, we show that, actually all convex regularizers and most nonconvex regularizers have this effect."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.08817","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1611.08817","created_at":"2026-05-18T00:13:19.735729+00:00"},{"alias_kind":"arxiv_version","alias_value":"1611.08817v3","created_at":"2026-05-18T00:13:19.735729+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.08817","created_at":"2026-05-18T00:13:19.735729+00:00"},{"alias_kind":"pith_short_12","alias_value":"XDUHGJV3SW2U","created_at":"2026-05-18T12:30:51.357362+00:00"},{"alias_kind":"pith_short_16","alias_value":"XDUHGJV3SW2UZN4Z","created_at":"2026-05-18T12:30:51.357362+00:00"},{"alias_kind":"pith_short_8","alias_value":"XDUHGJV3","created_at":"2026-05-18T12:30:51.357362+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XDUHGJV3SW2UZN4ZTYITYE45BW","json":"https://pith.science/pith/XDUHGJV3SW2UZN4ZTYITYE45BW.json","graph_json":"https://pith.science/api/pith-number/XDUHGJV3SW2UZN4ZTYITYE45BW/graph.json","events_json":"https://pith.science/api/pith-number/XDUHGJV3SW2UZN4ZTYITYE45BW/events.json","paper":"https://pith.science/paper/XDUHGJV3"},"agent_actions":{"view_html":"https://pith.science/pith/XDUHGJV3SW2UZN4ZTYITYE45BW","download_json":"https://pith.science/pith/XDUHGJV3SW2UZN4ZTYITYE45BW.json","view_paper":"https://pith.science/paper/XDUHGJV3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1611.08817&json=true","fetch_graph":"https://pith.science/api/pith-number/XDUHGJV3SW2UZN4ZTYITYE45BW/graph.json","fetch_events":"https://pith.science/api/pith-number/XDUHGJV3SW2UZN4ZTYITYE45BW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XDUHGJV3SW2UZN4ZTYITYE45BW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XDUHGJV3SW2UZN4ZTYITYE45BW/action/storage_attestation","attest_author":"https://pith.science/pith/XDUHGJV3SW2UZN4ZTYITYE45BW/action/author_attestation","sign_citation":"https://pith.science/pith/XDUHGJV3SW2UZN4ZTYITYE45BW/action/citation_signature","submit_replication":"https://pith.science/pith/XDUHGJV3SW2UZN4ZTYITYE45BW/action/replication_record"}},"created_at":"2026-05-18T00:13:19.735729+00:00","updated_at":"2026-05-18T00:13:19.735729+00:00"}