{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:TG3NRD75AM6QZYYEJL62HSN2PG","short_pith_number":"pith:TG3NRD75","canonical_record":{"source":{"id":"2402.15865","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-24T17:15:05Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"677326d5778a6882af202e3fdab56ab25ba08981cea5327c9d1401a55dba0f54","abstract_canon_sha256":"9c0767685ca7b8d7988985fa95bba1f381f3e9b23d62c2fca2697635f34e2d8d"},"schema_version":"1.0"},"canonical_sha256":"99b6d88ffd033d0ce3044afda3c9ba79a4fe332d4576ceaa4a08ec2b23fc1c4b","source":{"kind":"arxiv","id":"2402.15865","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.15865","created_at":"2026-07-05T07:48:59Z"},{"alias_kind":"arxiv_version","alias_value":"2402.15865v1","created_at":"2026-07-05T07:48:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.15865","created_at":"2026-07-05T07:48:59Z"},{"alias_kind":"pith_short_12","alias_value":"TG3NRD75AM6Q","created_at":"2026-07-05T07:48:59Z"},{"alias_kind":"pith_short_16","alias_value":"TG3NRD75AM6QZYYE","created_at":"2026-07-05T07:48:59Z"},{"alias_kind":"pith_short_8","alias_value":"TG3NRD75","created_at":"2026-07-05T07:48:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:TG3NRD75AM6QZYYEJL62HSN2PG","target":"record","payload":{"canonical_record":{"source":{"id":"2402.15865","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-24T17:15:05Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"677326d5778a6882af202e3fdab56ab25ba08981cea5327c9d1401a55dba0f54","abstract_canon_sha256":"9c0767685ca7b8d7988985fa95bba1f381f3e9b23d62c2fca2697635f34e2d8d"},"schema_version":"1.0"},"canonical_sha256":"99b6d88ffd033d0ce3044afda3c9ba79a4fe332d4576ceaa4a08ec2b23fc1c4b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:48:59.041536Z","signature_b64":"kUWWnZqaUpkYLfo/yyrLHV/Z/R+wz8qNhj1H6MN4OkHt/Ns4YvZGmpy6fmOuzJrkp9wp2F/KquojPCYQ6U/cBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"99b6d88ffd033d0ce3044afda3c9ba79a4fe332d4576ceaa4a08ec2b23fc1c4b","last_reissued_at":"2026-07-05T07:48:59.041059Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:48:59.041059Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.15865","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":"2026-07-05T07:48:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wyd4WxzWRiIut8tKGo+rub5JIPre+HQ2Qb3ZwTafXa039dGWKd5QnfwSX9j7AxdHPOwvLxToEHkas1lnSI0MAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T05:54:29.696114Z"},"content_sha256":"707295df88fbefd6703078d091dc37a3f1247597c3d2c69826340732f4ff9bd3","schema_version":"1.0","event_id":"sha256:707295df88fbefd6703078d091dc37a3f1247597c3d2c69826340732f4ff9bd3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:TG3NRD75AM6QZYYEJL62HSN2PG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"HIR-Diff: Unsupervised Hyperspectral Image Restoration Via Improved Diffusion Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Deyu Meng, Hongzhong Wang, Li Pang, Long Cui, Xiangyong Cao, Xiangyu Rui","submitted_at":"2024-02-24T17:15:05Z","abstract_excerpt":"Hyperspectral image (HSI) restoration aims at recovering clean images from degraded observations and plays a vital role in downstream tasks. Existing model-based methods have limitations in accurately modeling the complex image characteristics with handcraft priors, and deep learning-based methods suffer from poor generalization ability. To alleviate these issues, this paper proposes an unsupervised HSI restoration framework with pre-trained diffusion model (HIR-Diff), which restores the clean HSIs from the product of two low-rank components, i.e., the reduced image and the coefficient matrix."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.15865","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2402.15865/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T07:48:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gRfkwtz2B41sIkVoryCL5bArucy8XoRBt+FlYQJ7TrGxp1DGZHtJS7/aUHzDeTn0gihcgi4A+2/xOwWZ/ol9Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T05:54:29.696614Z"},"content_sha256":"bd2f6df05ec22afb2c564ff669b5ace9314395ea7ccf4dd9b6ea36a73a03c8f2","schema_version":"1.0","event_id":"sha256:bd2f6df05ec22afb2c564ff669b5ace9314395ea7ccf4dd9b6ea36a73a03c8f2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TG3NRD75AM6QZYYEJL62HSN2PG/bundle.json","state_url":"https://pith.science/pith/TG3NRD75AM6QZYYEJL62HSN2PG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TG3NRD75AM6QZYYEJL62HSN2PG/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":"2026-08-23T05:54:29Z","links":{"resolver":"https://pith.science/pith/TG3NRD75AM6QZYYEJL62HSN2PG","bundle":"https://pith.science/pith/TG3NRD75AM6QZYYEJL62HSN2PG/bundle.json","state":"https://pith.science/pith/TG3NRD75AM6QZYYEJL62HSN2PG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TG3NRD75AM6QZYYEJL62HSN2PG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:TG3NRD75AM6QZYYEJL62HSN2PG","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":"9c0767685ca7b8d7988985fa95bba1f381f3e9b23d62c2fca2697635f34e2d8d","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-24T17:15:05Z","title_canon_sha256":"677326d5778a6882af202e3fdab56ab25ba08981cea5327c9d1401a55dba0f54"},"schema_version":"1.0","source":{"id":"2402.15865","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.15865","created_at":"2026-07-05T07:48:59Z"},{"alias_kind":"arxiv_version","alias_value":"2402.15865v1","created_at":"2026-07-05T07:48:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.15865","created_at":"2026-07-05T07:48:59Z"},{"alias_kind":"pith_short_12","alias_value":"TG3NRD75AM6Q","created_at":"2026-07-05T07:48:59Z"},{"alias_kind":"pith_short_16","alias_value":"TG3NRD75AM6QZYYE","created_at":"2026-07-05T07:48:59Z"},{"alias_kind":"pith_short_8","alias_value":"TG3NRD75","created_at":"2026-07-05T07:48:59Z"}],"graph_snapshots":[{"event_id":"sha256:bd2f6df05ec22afb2c564ff669b5ace9314395ea7ccf4dd9b6ea36a73a03c8f2","target":"graph","created_at":"2026-07-05T07:48:59Z","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/2402.15865/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Hyperspectral image (HSI) restoration aims at recovering clean images from degraded observations and plays a vital role in downstream tasks. Existing model-based methods have limitations in accurately modeling the complex image characteristics with handcraft priors, and deep learning-based methods suffer from poor generalization ability. To alleviate these issues, this paper proposes an unsupervised HSI restoration framework with pre-trained diffusion model (HIR-Diff), which restores the clean HSIs from the product of two low-rank components, i.e., the reduced image and the coefficient matrix.","authors_text":"Deyu Meng, Hongzhong Wang, Li Pang, Long Cui, Xiangyong Cao, Xiangyu Rui","cross_cats":["eess.IV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-24T17:15:05Z","title":"HIR-Diff: Unsupervised Hyperspectral Image Restoration Via Improved Diffusion Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.15865","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":"sha256:707295df88fbefd6703078d091dc37a3f1247597c3d2c69826340732f4ff9bd3","target":"record","created_at":"2026-07-05T07:48:59Z","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":"9c0767685ca7b8d7988985fa95bba1f381f3e9b23d62c2fca2697635f34e2d8d","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-24T17:15:05Z","title_canon_sha256":"677326d5778a6882af202e3fdab56ab25ba08981cea5327c9d1401a55dba0f54"},"schema_version":"1.0","source":{"id":"2402.15865","kind":"arxiv","version":1}},"canonical_sha256":"99b6d88ffd033d0ce3044afda3c9ba79a4fe332d4576ceaa4a08ec2b23fc1c4b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"99b6d88ffd033d0ce3044afda3c9ba79a4fe332d4576ceaa4a08ec2b23fc1c4b","first_computed_at":"2026-07-05T07:48:59.041059Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:48:59.041059Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kUWWnZqaUpkYLfo/yyrLHV/Z/R+wz8qNhj1H6MN4OkHt/Ns4YvZGmpy6fmOuzJrkp9wp2F/KquojPCYQ6U/cBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:48:59.041536Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.15865","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:707295df88fbefd6703078d091dc37a3f1247597c3d2c69826340732f4ff9bd3","sha256:bd2f6df05ec22afb2c564ff669b5ace9314395ea7ccf4dd9b6ea36a73a03c8f2"],"state_sha256":"7652c8cb43a3e7eac713bdcf4199e28e56ef35ce0519704ae40ef8b63d8cd261"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BOJQBNRfbpgGGSB+IMYnGgyIQZN+WqGnz+twlYApwl9a4Y+p8kj8LPnlnje+1rCf5R0m8WXOIMrxo5BskEv5BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T05:54:29.701541Z","bundle_sha256":"c1a6566384a3e0829e593e8c9ab8be8cac5e5f2704421274f53040a5d7a742a8"}}