{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:5BKDHIZM6PWIEUB72PU7MXURPW","short_pith_number":"pith:5BKDHIZM","canonical_record":{"source":{"id":"1906.11827","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-21T15:25:19Z","cross_cats_sorted":[],"title_canon_sha256":"64b61430a447c59d0a59c80b74a851931009ad5ed6d7d56e5510bf1406129cbe","abstract_canon_sha256":"9ec63b439fcd57d748232a657e0ece05084ca1cecefd4f0b3dcefce9b30f20ac"},"schema_version":"1.0"},"canonical_sha256":"e85433a32cf3ec82503fd3e9f65e917db1f0c6fb27af1ab4fbfb7a8b973f79a5","source":{"kind":"arxiv","id":"1906.11827","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.11827","created_at":"2026-05-17T23:42:03Z"},{"alias_kind":"arxiv_version","alias_value":"1906.11827v1","created_at":"2026-05-17T23:42:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.11827","created_at":"2026-05-17T23:42:03Z"},{"alias_kind":"pith_short_12","alias_value":"5BKDHIZM6PWI","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"5BKDHIZM6PWIEUB7","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"5BKDHIZM","created_at":"2026-05-18T12:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:5BKDHIZM6PWIEUB72PU7MXURPW","target":"record","payload":{"canonical_record":{"source":{"id":"1906.11827","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-21T15:25:19Z","cross_cats_sorted":[],"title_canon_sha256":"64b61430a447c59d0a59c80b74a851931009ad5ed6d7d56e5510bf1406129cbe","abstract_canon_sha256":"9ec63b439fcd57d748232a657e0ece05084ca1cecefd4f0b3dcefce9b30f20ac"},"schema_version":"1.0"},"canonical_sha256":"e85433a32cf3ec82503fd3e9f65e917db1f0c6fb27af1ab4fbfb7a8b973f79a5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:42:03.675829Z","signature_b64":"DhzbPgzihbvoxyJih/ym+PWXgONrD30y7yu007bIyUvClGmnUDai6zHHs9kciAHAJIw6AA3Ed8x/UTw80VzJBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e85433a32cf3ec82503fd3e9f65e917db1f0c6fb27af1ab4fbfb7a8b973f79a5","last_reissued_at":"2026-05-17T23:42:03.675330Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:42:03.675330Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.11827","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:42:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jEhWUV4hQVXG46ml3RZ+7yScEqv8rp388XhdcnPx12xqA5ySaHqh7ZSyHkNDmUfiEZaKMDYcMRzaMddNuCKNAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T07:17:45.429155Z"},"content_sha256":"0ea7d32b62dc757cbfa7ecd9f097f5cd976be84f87ca8c7e9b2226460961590f","schema_version":"1.0","event_id":"sha256:0ea7d32b62dc757cbfa7ecd9f097f5cd976be84f87ca8c7e9b2226460961590f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:5BKDHIZM6PWIEUB72PU7MXURPW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Space-variant TV regularization for image restoration","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.IV","authors_text":"Alessandro Lanza, Fiorella Sgallari, Monica Pragliola, Serena Morigi","submitted_at":"2019-06-21T15:25:19Z","abstract_excerpt":"We propose two new variational models aimed to outperform the popular total variation (TV) model for image restoration with L$_2$ and L$_1$ fidelity terms. In particular, we introduce a space-variant generalization of the TV regularizer, referred to as TV$_p^{SV}$, where the so-called shape parameter $p\\,$ is automatically and locally estimated by applying a statistical inference technique based on the generalized Gaussian distribution. The restored image is efficiently computed by using an alternating direction method of multipliers procedure. We validated our models on images corrupted by Ga"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.11827","kind":"arxiv","version":1},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:42:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I+Fodg2BpTMT0jFTQMF8ZFc0g9Q8ij3fliiDeJJtBGK3rBq0pVyefO6+GqiiAVb+W7Oui15Dd/IIrUfdfc1oBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T07:17:45.429868Z"},"content_sha256":"45ee724cd542b6c6bc3243c988834549404bfe1129ccf27bd8b8c096e5741032","schema_version":"1.0","event_id":"sha256:45ee724cd542b6c6bc3243c988834549404bfe1129ccf27bd8b8c096e5741032"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5BKDHIZM6PWIEUB72PU7MXURPW/bundle.json","state_url":"https://pith.science/pith/5BKDHIZM6PWIEUB72PU7MXURPW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5BKDHIZM6PWIEUB72PU7MXURPW/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-31T07:17:45Z","links":{"resolver":"https://pith.science/pith/5BKDHIZM6PWIEUB72PU7MXURPW","bundle":"https://pith.science/pith/5BKDHIZM6PWIEUB72PU7MXURPW/bundle.json","state":"https://pith.science/pith/5BKDHIZM6PWIEUB72PU7MXURPW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5BKDHIZM6PWIEUB72PU7MXURPW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:5BKDHIZM6PWIEUB72PU7MXURPW","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"9ec63b439fcd57d748232a657e0ece05084ca1cecefd4f0b3dcefce9b30f20ac","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-21T15:25:19Z","title_canon_sha256":"64b61430a447c59d0a59c80b74a851931009ad5ed6d7d56e5510bf1406129cbe"},"schema_version":"1.0","source":{"id":"1906.11827","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.11827","created_at":"2026-05-17T23:42:03Z"},{"alias_kind":"arxiv_version","alias_value":"1906.11827v1","created_at":"2026-05-17T23:42:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.11827","created_at":"2026-05-17T23:42:03Z"},{"alias_kind":"pith_short_12","alias_value":"5BKDHIZM6PWI","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"5BKDHIZM6PWIEUB7","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"5BKDHIZM","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:45ee724cd542b6c6bc3243c988834549404bfe1129ccf27bd8b8c096e5741032","target":"graph","created_at":"2026-05-17T23:42:03Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"We propose two new variational models aimed to outperform the popular total variation (TV) model for image restoration with L$_2$ and L$_1$ fidelity terms. In particular, we introduce a space-variant generalization of the TV regularizer, referred to as TV$_p^{SV}$, where the so-called shape parameter $p\\,$ is automatically and locally estimated by applying a statistical inference technique based on the generalized Gaussian distribution. The restored image is efficiently computed by using an alternating direction method of multipliers procedure. We validated our models on images corrupted by Ga","authors_text":"Alessandro Lanza, Fiorella Sgallari, Monica Pragliola, Serena Morigi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-21T15:25:19Z","title":"Space-variant TV regularization for image restoration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.11827","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:0ea7d32b62dc757cbfa7ecd9f097f5cd976be84f87ca8c7e9b2226460961590f","target":"record","created_at":"2026-05-17T23:42:03Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"9ec63b439fcd57d748232a657e0ece05084ca1cecefd4f0b3dcefce9b30f20ac","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-21T15:25:19Z","title_canon_sha256":"64b61430a447c59d0a59c80b74a851931009ad5ed6d7d56e5510bf1406129cbe"},"schema_version":"1.0","source":{"id":"1906.11827","kind":"arxiv","version":1}},"canonical_sha256":"e85433a32cf3ec82503fd3e9f65e917db1f0c6fb27af1ab4fbfb7a8b973f79a5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e85433a32cf3ec82503fd3e9f65e917db1f0c6fb27af1ab4fbfb7a8b973f79a5","first_computed_at":"2026-05-17T23:42:03.675330Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:42:03.675330Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DhzbPgzihbvoxyJih/ym+PWXgONrD30y7yu007bIyUvClGmnUDai6zHHs9kciAHAJIw6AA3Ed8x/UTw80VzJBQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:42:03.675829Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.11827","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0ea7d32b62dc757cbfa7ecd9f097f5cd976be84f87ca8c7e9b2226460961590f","sha256:45ee724cd542b6c6bc3243c988834549404bfe1129ccf27bd8b8c096e5741032"],"state_sha256":"fb3a4dd2b997b7a163b6b515c7070fa5ac456050c3f76495140768622be8da1b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TQOnd8gaSCyH+d7F1c9xDVafoMfDNfNiy/Q+D001NZF+EQvvs22jtc+N1+d1/kHf+5aQTajpghXTizkVqNQvBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T07:17:45.433564Z","bundle_sha256":"c4c5314186a1d7bc74942767daa041531d398730ee5fa65427a0727e700b6fb7"}}