{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:RSJEKBNWAR7SZ2NYOBMUEGGSQL","short_pith_number":"pith:RSJEKBNW","canonical_record":{"source":{"id":"1901.06112","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-18T07:24:28Z","cross_cats_sorted":[],"title_canon_sha256":"fa65d494d32ee1822313be069700e3092b1e91e7722c410ca5d13b5bba762356","abstract_canon_sha256":"bcb0dfe2439eac08a1176328d3f443909cb0790a246f1265c80b8aa174a467c6"},"schema_version":"1.0"},"canonical_sha256":"8c924505b6047f2ce9b870594218d282e810e81b09bd5edf9f4130156bcf8be3","source":{"kind":"arxiv","id":"1901.06112","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.06112","created_at":"2026-05-17T23:53:20Z"},{"alias_kind":"arxiv_version","alias_value":"1901.06112v1","created_at":"2026-05-17T23:53:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.06112","created_at":"2026-05-17T23:53:20Z"},{"alias_kind":"pith_short_12","alias_value":"RSJEKBNWAR7S","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"RSJEKBNWAR7SZ2NY","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"RSJEKBNW","created_at":"2026-05-18T12:33:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:RSJEKBNWAR7SZ2NYOBMUEGGSQL","target":"record","payload":{"canonical_record":{"source":{"id":"1901.06112","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-18T07:24:28Z","cross_cats_sorted":[],"title_canon_sha256":"fa65d494d32ee1822313be069700e3092b1e91e7722c410ca5d13b5bba762356","abstract_canon_sha256":"bcb0dfe2439eac08a1176328d3f443909cb0790a246f1265c80b8aa174a467c6"},"schema_version":"1.0"},"canonical_sha256":"8c924505b6047f2ce9b870594218d282e810e81b09bd5edf9f4130156bcf8be3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:53:20.798763Z","signature_b64":"j5kZg+hafqyH8ZcLRafYOYLqQwmqsNYarC3RIhCvevBfRFF8TWDouhpJAZn4CStKTqcdoeqy59gsmL9/H/fLCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8c924505b6047f2ce9b870594218d282e810e81b09bd5edf9f4130156bcf8be3","last_reissued_at":"2026-05-17T23:53:20.798182Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:53:20.798182Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1901.06112","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":"2026-05-17T23:53:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sqdfxtdBp6Lk1NQMS0vxhh8HN8eU6aPZRnu0KxRpeFY9xJXHUEb4ZLeHVF6x1X0si4J/TryetxazQ8NZPY5HDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T17:46:25.148223Z"},"content_sha256":"fc60225545e8decfe17023a3ceb15997fc95f5979019ec976577bf7ac97c1c09","schema_version":"1.0","event_id":"sha256:fc60225545e8decfe17023a3ceb15997fc95f5979019ec976577bf7ac97c1c09"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:RSJEKBNWAR7SZ2NYOBMUEGGSQL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fast High-Dimensional Kernel Filtering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kunal N. Chaudhury, Pravin Nair","submitted_at":"2019-01-18T07:24:28Z","abstract_excerpt":"The bilateral and nonlocal means filters are instances of kernel-based filters that are popularly used in image processing. It was recently shown that fast and accurate bilateral filtering of grayscale images can be performed using a low-rank approximation of the kernel matrix. More specifically, based on the eigendecomposition of the kernel matrix, the overall filtering was approximated using spatial convolutions, for which efficient algorithms are available. Unfortunately, this technique cannot be scaled to high-dimensional data such as color and hyperspectral images. This is simply because "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.06112","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":"2026-05-17T23:53:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qpYlJkeBEU0h5bJ9JzRxb/0eaUmGdwR6VsX502U3R0duhL63WUvJ+oxtIxdpcQERzdyWveXiAUMP1gZv5+6YBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T17:46:25.148582Z"},"content_sha256":"8151a469404dde6d71da6e4441e2c0e893b6cc2151a0cbffb8e39a9f401ab0b9","schema_version":"1.0","event_id":"sha256:8151a469404dde6d71da6e4441e2c0e893b6cc2151a0cbffb8e39a9f401ab0b9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RSJEKBNWAR7SZ2NYOBMUEGGSQL/bundle.json","state_url":"https://pith.science/pith/RSJEKBNWAR7SZ2NYOBMUEGGSQL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RSJEKBNWAR7SZ2NYOBMUEGGSQL/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":"2026-06-28T17:46:25Z","links":{"resolver":"https://pith.science/pith/RSJEKBNWAR7SZ2NYOBMUEGGSQL","bundle":"https://pith.science/pith/RSJEKBNWAR7SZ2NYOBMUEGGSQL/bundle.json","state":"https://pith.science/pith/RSJEKBNWAR7SZ2NYOBMUEGGSQL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RSJEKBNWAR7SZ2NYOBMUEGGSQL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:RSJEKBNWAR7SZ2NYOBMUEGGSQL","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":"bcb0dfe2439eac08a1176328d3f443909cb0790a246f1265c80b8aa174a467c6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-18T07:24:28Z","title_canon_sha256":"fa65d494d32ee1822313be069700e3092b1e91e7722c410ca5d13b5bba762356"},"schema_version":"1.0","source":{"id":"1901.06112","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.06112","created_at":"2026-05-17T23:53:20Z"},{"alias_kind":"arxiv_version","alias_value":"1901.06112v1","created_at":"2026-05-17T23:53:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.06112","created_at":"2026-05-17T23:53:20Z"},{"alias_kind":"pith_short_12","alias_value":"RSJEKBNWAR7S","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"RSJEKBNWAR7SZ2NY","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"RSJEKBNW","created_at":"2026-05-18T12:33:27Z"}],"graph_snapshots":[{"event_id":"sha256:8151a469404dde6d71da6e4441e2c0e893b6cc2151a0cbffb8e39a9f401ab0b9","target":"graph","created_at":"2026-05-17T23:53:20Z","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":"The bilateral and nonlocal means filters are instances of kernel-based filters that are popularly used in image processing. It was recently shown that fast and accurate bilateral filtering of grayscale images can be performed using a low-rank approximation of the kernel matrix. More specifically, based on the eigendecomposition of the kernel matrix, the overall filtering was approximated using spatial convolutions, for which efficient algorithms are available. Unfortunately, this technique cannot be scaled to high-dimensional data such as color and hyperspectral images. This is simply because ","authors_text":"Kunal N. Chaudhury, Pravin Nair","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-18T07:24:28Z","title":"Fast High-Dimensional Kernel Filtering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.06112","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:fc60225545e8decfe17023a3ceb15997fc95f5979019ec976577bf7ac97c1c09","target":"record","created_at":"2026-05-17T23:53:20Z","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":"bcb0dfe2439eac08a1176328d3f443909cb0790a246f1265c80b8aa174a467c6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-18T07:24:28Z","title_canon_sha256":"fa65d494d32ee1822313be069700e3092b1e91e7722c410ca5d13b5bba762356"},"schema_version":"1.0","source":{"id":"1901.06112","kind":"arxiv","version":1}},"canonical_sha256":"8c924505b6047f2ce9b870594218d282e810e81b09bd5edf9f4130156bcf8be3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8c924505b6047f2ce9b870594218d282e810e81b09bd5edf9f4130156bcf8be3","first_computed_at":"2026-05-17T23:53:20.798182Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:53:20.798182Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"j5kZg+hafqyH8ZcLRafYOYLqQwmqsNYarC3RIhCvevBfRFF8TWDouhpJAZn4CStKTqcdoeqy59gsmL9/H/fLCg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:53:20.798763Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.06112","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fc60225545e8decfe17023a3ceb15997fc95f5979019ec976577bf7ac97c1c09","sha256:8151a469404dde6d71da6e4441e2c0e893b6cc2151a0cbffb8e39a9f401ab0b9"],"state_sha256":"836926251db0fd70bf9f112bb7db30b4bee9e2cae643591a8d3e4a0155fbdef6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mBuhCqo4CeuS3Kh27zAB/95yNssAmH/Q1gXYVvDU6vgmv5zqLHoSxLOY+xlcQEf+sTAfUsjGnwaFptTrUWqHAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-28T17:46:25.150454Z","bundle_sha256":"0094c9119b9642828d5e46cae50fe7455a2d0065b21d3f9af23bb7d7afe7fdc9"}}