{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:JYBP6PQCXYH5NNHOZH5XK7QFDK","short_pith_number":"pith:JYBP6PQC","canonical_record":{"source":{"id":"2305.10925","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-18T12:38:29Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"efaab08a2792efeb853567096016a33d182f5ec8a6884e3318ec165a8c7dff10","abstract_canon_sha256":"f1efa72502de442810e529686a40fa4defe91685cd4ac74be3a32b14f9eabe1b"},"schema_version":"1.0"},"canonical_sha256":"4e02ff3e02be0fd6b4eec9fb757e051aa50b78769dec41a50ec6cb18ab78979f","source":{"kind":"arxiv","id":"2305.10925","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.10925","created_at":"2026-07-05T07:14:12Z"},{"alias_kind":"arxiv_version","alias_value":"2305.10925v2","created_at":"2026-07-05T07:14:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.10925","created_at":"2026-07-05T07:14:12Z"},{"alias_kind":"pith_short_12","alias_value":"JYBP6PQCXYH5","created_at":"2026-07-05T07:14:12Z"},{"alias_kind":"pith_short_16","alias_value":"JYBP6PQCXYH5NNHO","created_at":"2026-07-05T07:14:12Z"},{"alias_kind":"pith_short_8","alias_value":"JYBP6PQC","created_at":"2026-07-05T07:14:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:JYBP6PQCXYH5NNHOZH5XK7QFDK","target":"record","payload":{"canonical_record":{"source":{"id":"2305.10925","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-18T12:38:29Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"efaab08a2792efeb853567096016a33d182f5ec8a6884e3318ec165a8c7dff10","abstract_canon_sha256":"f1efa72502de442810e529686a40fa4defe91685cd4ac74be3a32b14f9eabe1b"},"schema_version":"1.0"},"canonical_sha256":"4e02ff3e02be0fd6b4eec9fb757e051aa50b78769dec41a50ec6cb18ab78979f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:14:12.168298Z","signature_b64":"YPcN6o2nE0MesbvanXpI+vIKrSsJOKd72zem8wHSewwk+aYMdv9f1KpAACoT8p3Rp2l6TFinN+C0Uc62sOqyAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4e02ff3e02be0fd6b4eec9fb757e051aa50b78769dec41a50ec6cb18ab78979f","last_reissued_at":"2026-07-05T07:14:12.167806Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:14:12.167806Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.10925","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:14:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/+zK0rl8GfXI7VXLmoG9jmYCntEDGP3MZroYafJB8wrHOhxxajInW+ErPw8aNKGZrIGFN5UfsY25lbVrzquKCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T18:49:52.727654Z"},"content_sha256":"b6f16e3e4ff1ea461180398545a8f44b1859a52ca489879a89471c5d34bbe324","schema_version":"1.0","event_id":"sha256:b6f16e3e4ff1ea461180398545a8f44b1859a52ca489879a89471c5d34bbe324"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:JYBP6PQCXYH5NNHOZH5XK7QFDK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised Hyperspectral Pansharpening via Low-rank Diffusion Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Deyu Meng, Li Pang, Xiangyong Cao, Xiangyu Rui, Zeyu Zhu, Zongsheng Yue","submitted_at":"2023-05-18T12:38:29Z","abstract_excerpt":"Hyperspectral pansharpening is a process of merging a high-resolution panchromatic (PAN) image and a low-resolution hyperspectral (LRHS) image to create a single high-resolution hyperspectral (HRHS) image. Existing Bayesian-based HS pansharpening methods require designing handcraft image prior to characterize the image features, and deep learning-based HS pansharpening methods usually require a large number of paired training data and suffer from poor generalization ability. To address these issues, in this work, we propose a low-rank diffusion model for hyperspectral pansharpening by simultan"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.10925","kind":"arxiv","version":2},"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/2305.10925/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":"2026-07-05T07:14:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KFS0IVkPXe9Vgbg6PmQnkq+EHwyJvLlwDDrS6HN2J6Enia13HlROBDbUi+ZK3ZLGRUP1Or5KuWbKbowMvo/0BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T18:49:52.728802Z"},"content_sha256":"d74a3df869cecc6e3417d28f510b5d2621e79a1075c355d94240692981bdebf4","schema_version":"1.0","event_id":"sha256:d74a3df869cecc6e3417d28f510b5d2621e79a1075c355d94240692981bdebf4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JYBP6PQCXYH5NNHOZH5XK7QFDK/bundle.json","state_url":"https://pith.science/pith/JYBP6PQCXYH5NNHOZH5XK7QFDK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JYBP6PQCXYH5NNHOZH5XK7QFDK/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":"2026-08-22T18:49:52Z","links":{"resolver":"https://pith.science/pith/JYBP6PQCXYH5NNHOZH5XK7QFDK","bundle":"https://pith.science/pith/JYBP6PQCXYH5NNHOZH5XK7QFDK/bundle.json","state":"https://pith.science/pith/JYBP6PQCXYH5NNHOZH5XK7QFDK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JYBP6PQCXYH5NNHOZH5XK7QFDK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:JYBP6PQCXYH5NNHOZH5XK7QFDK","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":"f1efa72502de442810e529686a40fa4defe91685cd4ac74be3a32b14f9eabe1b","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-18T12:38:29Z","title_canon_sha256":"efaab08a2792efeb853567096016a33d182f5ec8a6884e3318ec165a8c7dff10"},"schema_version":"1.0","source":{"id":"2305.10925","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.10925","created_at":"2026-07-05T07:14:12Z"},{"alias_kind":"arxiv_version","alias_value":"2305.10925v2","created_at":"2026-07-05T07:14:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.10925","created_at":"2026-07-05T07:14:12Z"},{"alias_kind":"pith_short_12","alias_value":"JYBP6PQCXYH5","created_at":"2026-07-05T07:14:12Z"},{"alias_kind":"pith_short_16","alias_value":"JYBP6PQCXYH5NNHO","created_at":"2026-07-05T07:14:12Z"},{"alias_kind":"pith_short_8","alias_value":"JYBP6PQC","created_at":"2026-07-05T07:14:12Z"}],"graph_snapshots":[{"event_id":"sha256:d74a3df869cecc6e3417d28f510b5d2621e79a1075c355d94240692981bdebf4","target":"graph","created_at":"2026-07-05T07:14:12Z","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/2305.10925/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Hyperspectral pansharpening is a process of merging a high-resolution panchromatic (PAN) image and a low-resolution hyperspectral (LRHS) image to create a single high-resolution hyperspectral (HRHS) image. Existing Bayesian-based HS pansharpening methods require designing handcraft image prior to characterize the image features, and deep learning-based HS pansharpening methods usually require a large number of paired training data and suffer from poor generalization ability. To address these issues, in this work, we propose a low-rank diffusion model for hyperspectral pansharpening by simultan","authors_text":"Deyu Meng, Li Pang, Xiangyong Cao, Xiangyu Rui, Zeyu Zhu, Zongsheng Yue","cross_cats":["eess.IV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-18T12:38:29Z","title":"Unsupervised Hyperspectral Pansharpening via Low-rank Diffusion Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.10925","kind":"arxiv","version":2},"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:b6f16e3e4ff1ea461180398545a8f44b1859a52ca489879a89471c5d34bbe324","target":"record","created_at":"2026-07-05T07:14:12Z","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":"f1efa72502de442810e529686a40fa4defe91685cd4ac74be3a32b14f9eabe1b","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-18T12:38:29Z","title_canon_sha256":"efaab08a2792efeb853567096016a33d182f5ec8a6884e3318ec165a8c7dff10"},"schema_version":"1.0","source":{"id":"2305.10925","kind":"arxiv","version":2}},"canonical_sha256":"4e02ff3e02be0fd6b4eec9fb757e051aa50b78769dec41a50ec6cb18ab78979f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4e02ff3e02be0fd6b4eec9fb757e051aa50b78769dec41a50ec6cb18ab78979f","first_computed_at":"2026-07-05T07:14:12.167806Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:14:12.167806Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YPcN6o2nE0MesbvanXpI+vIKrSsJOKd72zem8wHSewwk+aYMdv9f1KpAACoT8p3Rp2l6TFinN+C0Uc62sOqyAg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:14:12.168298Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.10925","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b6f16e3e4ff1ea461180398545a8f44b1859a52ca489879a89471c5d34bbe324","sha256:d74a3df869cecc6e3417d28f510b5d2621e79a1075c355d94240692981bdebf4"],"state_sha256":"c2a883a801f74f5d3b9ac616b637b4f858c612690d181425c21c6ad4d279a939"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"24z7X7njQYK42sSp4XOiMEj9Xj17G1AW40eXNYSyNovI7SIk7T54QdCW2QkbBtPft8HCLQSwOuoUZvkOFhUjDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T18:49:52.733939Z","bundle_sha256":"344b5b3cf03cfe21e2ab88d958d3c8721f1fbe3e346ffcbc630ecb79c12bd50a"}}