{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:ODXDUCTFFBI5K6FOQJDTIQHCDO","short_pith_number":"pith:ODXDUCTF","canonical_record":{"source":{"id":"1403.2482","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-03-11T06:48:58Z","cross_cats_sorted":[],"title_canon_sha256":"678ba3bc14f7e077f63d9719152d6a04265b61a8749a5c6fd1bcc8d880f29726","abstract_canon_sha256":"dbb9aeec82a371794ea94b9b7b5d02aa93f9e0fe0d3b60d0a7a092e0436dcb49"},"schema_version":"1.0"},"canonical_sha256":"70ee3a0a652851d578ae82473440e21bbe8f432b4fa87f5cf2b93b5495732fe8","source":{"kind":"arxiv","id":"1403.2482","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1403.2482","created_at":"2026-05-18T02:56:43Z"},{"alias_kind":"arxiv_version","alias_value":"1403.2482v1","created_at":"2026-05-18T02:56:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1403.2482","created_at":"2026-05-18T02:56:43Z"},{"alias_kind":"pith_short_12","alias_value":"ODXDUCTFFBI5","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_16","alias_value":"ODXDUCTFFBI5K6FO","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_8","alias_value":"ODXDUCTF","created_at":"2026-05-18T12:28:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:ODXDUCTFFBI5K6FOQJDTIQHCDO","target":"record","payload":{"canonical_record":{"source":{"id":"1403.2482","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-03-11T06:48:58Z","cross_cats_sorted":[],"title_canon_sha256":"678ba3bc14f7e077f63d9719152d6a04265b61a8749a5c6fd1bcc8d880f29726","abstract_canon_sha256":"dbb9aeec82a371794ea94b9b7b5d02aa93f9e0fe0d3b60d0a7a092e0436dcb49"},"schema_version":"1.0"},"canonical_sha256":"70ee3a0a652851d578ae82473440e21bbe8f432b4fa87f5cf2b93b5495732fe8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:56:43.218986Z","signature_b64":"BRid1xou9cdrlYFpa6CHktQ9V0IJ0nwOV9UBWexgaNe//gfjjIE//i0mWZgP38liQg0WNsKEECflEzyzSGl4DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"70ee3a0a652851d578ae82473440e21bbe8f432b4fa87f5cf2b93b5495732fe8","last_reissued_at":"2026-05-18T02:56:43.218533Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:56:43.218533Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1403.2482","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":"2026-05-18T02:56:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R7SFRJCEuUrvHgG+PQ53svFVOZu9QnIgjGgtthgXGtxNFvYGckzUpMDbi9A3nBOI90WsktaiYBw5R/Mq4LloAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T22:43:21.542894Z"},"content_sha256":"c22d0aeb3be37fa1bbfa5a29ab85561f2954b7b76edb86817dbee88494ac966c","schema_version":"1.0","event_id":"sha256:c22d0aeb3be37fa1bbfa5a29ab85561f2954b7b76edb86817dbee88494ac966c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:ODXDUCTFFBI5K6FOQJDTIQHCDO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Removing Mixture of Gaussian and Impulse Noise by Patch-Based Weighted Means","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bing Li, Haijuan Hu, Quansheng Liu","submitted_at":"2014-03-11T06:48:58Z","abstract_excerpt":"We first establish a law of large numbers and a convergence theorem in distribution to show the rate of convergence of the non-local means filter for removing Gaussian noise. We then introduce the notion of degree of similarity to measure the role of similarity for the non-local means filter. Based on the convergence theorems, we propose a patch-based weighted means filter for removing impulse noise and its mixture with Gaussian noise by combining the essential idea of the trilateral filter and that of the non-local means filter. Our experiments show that our filter is competitive compared to "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1403.2482","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":"2026-05-18T02:56:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IiBmRofgY9dCXGX9FCxQrxSGsLeAr7AhIlQluIcZAa6vJT88QLaAGrb67GTyFC9cmZddmWpMBGgehebHYWRQDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T22:43:21.543233Z"},"content_sha256":"50005cc3cb5071e240ec2ce18739aee8f16d52a929a55d326a17b70a70b31aa3","schema_version":"1.0","event_id":"sha256:50005cc3cb5071e240ec2ce18739aee8f16d52a929a55d326a17b70a70b31aa3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ODXDUCTFFBI5K6FOQJDTIQHCDO/bundle.json","state_url":"https://pith.science/pith/ODXDUCTFFBI5K6FOQJDTIQHCDO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ODXDUCTFFBI5K6FOQJDTIQHCDO/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":"2026-06-22T22:43:21Z","links":{"resolver":"https://pith.science/pith/ODXDUCTFFBI5K6FOQJDTIQHCDO","bundle":"https://pith.science/pith/ODXDUCTFFBI5K6FOQJDTIQHCDO/bundle.json","state":"https://pith.science/pith/ODXDUCTFFBI5K6FOQJDTIQHCDO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ODXDUCTFFBI5K6FOQJDTIQHCDO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:ODXDUCTFFBI5K6FOQJDTIQHCDO","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":"dbb9aeec82a371794ea94b9b7b5d02aa93f9e0fe0d3b60d0a7a092e0436dcb49","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-03-11T06:48:58Z","title_canon_sha256":"678ba3bc14f7e077f63d9719152d6a04265b61a8749a5c6fd1bcc8d880f29726"},"schema_version":"1.0","source":{"id":"1403.2482","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1403.2482","created_at":"2026-05-18T02:56:43Z"},{"alias_kind":"arxiv_version","alias_value":"1403.2482v1","created_at":"2026-05-18T02:56:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1403.2482","created_at":"2026-05-18T02:56:43Z"},{"alias_kind":"pith_short_12","alias_value":"ODXDUCTFFBI5","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_16","alias_value":"ODXDUCTFFBI5K6FO","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_8","alias_value":"ODXDUCTF","created_at":"2026-05-18T12:28:41Z"}],"graph_snapshots":[{"event_id":"sha256:50005cc3cb5071e240ec2ce18739aee8f16d52a929a55d326a17b70a70b31aa3","target":"graph","created_at":"2026-05-18T02:56:43Z","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 first establish a law of large numbers and a convergence theorem in distribution to show the rate of convergence of the non-local means filter for removing Gaussian noise. We then introduce the notion of degree of similarity to measure the role of similarity for the non-local means filter. Based on the convergence theorems, we propose a patch-based weighted means filter for removing impulse noise and its mixture with Gaussian noise by combining the essential idea of the trilateral filter and that of the non-local means filter. Our experiments show that our filter is competitive compared to ","authors_text":"Bing Li, Haijuan Hu, Quansheng Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-03-11T06:48:58Z","title":"Removing Mixture of Gaussian and Impulse Noise by Patch-Based Weighted Means"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1403.2482","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:c22d0aeb3be37fa1bbfa5a29ab85561f2954b7b76edb86817dbee88494ac966c","target":"record","created_at":"2026-05-18T02:56:43Z","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":"dbb9aeec82a371794ea94b9b7b5d02aa93f9e0fe0d3b60d0a7a092e0436dcb49","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-03-11T06:48:58Z","title_canon_sha256":"678ba3bc14f7e077f63d9719152d6a04265b61a8749a5c6fd1bcc8d880f29726"},"schema_version":"1.0","source":{"id":"1403.2482","kind":"arxiv","version":1}},"canonical_sha256":"70ee3a0a652851d578ae82473440e21bbe8f432b4fa87f5cf2b93b5495732fe8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"70ee3a0a652851d578ae82473440e21bbe8f432b4fa87f5cf2b93b5495732fe8","first_computed_at":"2026-05-18T02:56:43.218533Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:56:43.218533Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BRid1xou9cdrlYFpa6CHktQ9V0IJ0nwOV9UBWexgaNe//gfjjIE//i0mWZgP38liQg0WNsKEECflEzyzSGl4DQ==","signature_status":"signed_v1","signed_at":"2026-05-18T02:56:43.218986Z","signed_message":"canonical_sha256_bytes"},"source_id":"1403.2482","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c22d0aeb3be37fa1bbfa5a29ab85561f2954b7b76edb86817dbee88494ac966c","sha256:50005cc3cb5071e240ec2ce18739aee8f16d52a929a55d326a17b70a70b31aa3"],"state_sha256":"75d9ca0e36133c0252b9eb9e9fd0eb5f043cd2597270e0833712ac42e637076a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jeFF8/caML5VsjF+xT3Pa7AY4r+O326v71wu6BC3wMTjULXY3jCjF9niwVngg7LRasdnLsmQQCzbzo43TBJ0DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-22T22:43:21.545354Z","bundle_sha256":"ba47b6eed7dcc6aa2b96537ee7f317367c3ef8a4fbfcc5596ce309f724c6da45"}}