{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:TFLZONLHO2U7FPYI3PQGQJNWM5","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":"8b011f5888b62a418f629678bd7bb502bfe9743a341cc7bc64dddd1e926faa30","cross_cats_sorted":["cs.LG","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-07-10T13:10:27Z","title_canon_sha256":"a846c00b88c0ace8ec25df14b699a2c132099fde4bbb1f713c56db82d96b14b3"},"schema_version":"1.0","source":{"id":"1907.04699","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.04699","created_at":"2026-07-05T01:05:09Z"},{"alias_kind":"arxiv_version","alias_value":"1907.04699v3","created_at":"2026-07-05T01:05:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.04699","created_at":"2026-07-05T01:05:09Z"},{"alias_kind":"pith_short_12","alias_value":"TFLZONLHO2U7","created_at":"2026-07-05T01:05:09Z"},{"alias_kind":"pith_short_16","alias_value":"TFLZONLHO2U7FPYI","created_at":"2026-07-05T01:05:09Z"},{"alias_kind":"pith_short_8","alias_value":"TFLZONLH","created_at":"2026-07-05T01:05:09Z"}],"graph_snapshots":[{"event_id":"sha256:778bb2dfd5abb46766ee8dc20b2e2195cc2db90d2a8a9876f0a53e2902d688e1","target":"graph","created_at":"2026-07-05T01:05:09Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1907.04699/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, low-rank matrix recovery theory has been emerging as a significant progress for various image processing problems. Meanwhile, the group sparse coding (GSC) theory has led to great successes in image restoration (IR) problem with each group contains low-rank property. In this paper, we propose a novel low-rank minimization based denoising model for IR tasks under the perspective of GSC, an important connection between our denoising model and rank minimization problem has been put forward. To overcome the bias problem caused by convex nuclear norm minimization (NNM) for rank approximat","authors_text":"Guan Gui, Xiefeng Cheng, Yunyi Li","cross_cats":["cs.LG","eess.SP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-07-10T13:10:27Z","title":"From Group Sparse Coding to Rank Minimization: A Novel Denoising Model for Low-level Image Restoration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.04699","kind":"arxiv","version":3},"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":"sha256:65b8555ad9ffc1f154db1f4ecd00df68e1fcea33c2662e64185f5480f678d9af","target":"record","created_at":"2026-07-05T01:05:09Z","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":"8b011f5888b62a418f629678bd7bb502bfe9743a341cc7bc64dddd1e926faa30","cross_cats_sorted":["cs.LG","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-07-10T13:10:27Z","title_canon_sha256":"a846c00b88c0ace8ec25df14b699a2c132099fde4bbb1f713c56db82d96b14b3"},"schema_version":"1.0","source":{"id":"1907.04699","kind":"arxiv","version":3}},"canonical_sha256":"995797356776a9f2bf08dbe06825b6674592bb2f4e6d7fa40d6ca157502d42d5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"995797356776a9f2bf08dbe06825b6674592bb2f4e6d7fa40d6ca157502d42d5","first_computed_at":"2026-07-05T01:05:09.441365Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:05:09.441365Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rMqK3XL12tec8TjBWCpSeyFlEJxKOg7WzcZlwDstlTeS8XX2d3hRviSDiFC6/hm0m3oQ4OmDrpu+qE3Wb+e+CA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:05:09.441764Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.04699","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:65b8555ad9ffc1f154db1f4ecd00df68e1fcea33c2662e64185f5480f678d9af","sha256:778bb2dfd5abb46766ee8dc20b2e2195cc2db90d2a8a9876f0a53e2902d688e1"],"state_sha256":"520dfc9ab7ad886764f0119fc316ee4be0adb3030458f263d6e7ba6d1ccea71e"}