{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:N355KNDSDIB4UCCO2OZHJX2ASO","short_pith_number":"pith:N355KNDS","schema_version":"1.0","canonical_sha256":"6efbd534721a03ca084ed3b274df4093b4bc7c4c8aeb14cd5e75995142b49a87","source":{"kind":"arxiv","id":"1503.07297","version":1},"attestation_state":"computed","paper":{"title":"A Brief Survey of Recent Edge-Preserving Smoothing Algorithms on Digital Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Amlan Chakrabarti, Chandrajit pal, Ranjan Ghosh","submitted_at":"2015-03-25T07:16:35Z","abstract_excerpt":"Edge preserving filters preserve the edges and its information while blurring an image. In other words they are used to smooth an image, while reducing the edge blurring effects across the edge like halos, phantom etc. They are nonlinear in nature. Examples are bilateral filter, anisotropic diffusion filter, guided filter, trilateral filter etc. Hence these family of filters are very useful in reducing the noise in an image making it very demanding in computer vision and computational photography applications like denoising, video abstraction, demosaicing, optical-flow estimation, stereo match"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1503.07297","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-03-25T07:16:35Z","cross_cats_sorted":[],"title_canon_sha256":"d82690142fd9943bd4010f000aeecf9f36660ccb3546edcc5dc1d1f912b8f903","abstract_canon_sha256":"18438500a623c445134f94b5f14fe1664c7b6d12097d2a5d536410d8abb269dc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:20:21.538431Z","signature_b64":"KOKP5coIJagzAjPYCNqcNtswP2bNf/bM3hpdcXpKyYfZUJIUrXuZrprtWcqixM9whAbqWxbQv4RYbQmBcPP8Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6efbd534721a03ca084ed3b274df4093b4bc7c4c8aeb14cd5e75995142b49a87","last_reissued_at":"2026-05-18T02:20:21.537685Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:20:21.537685Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Brief Survey of Recent Edge-Preserving Smoothing Algorithms on Digital Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Amlan Chakrabarti, Chandrajit pal, Ranjan Ghosh","submitted_at":"2015-03-25T07:16:35Z","abstract_excerpt":"Edge preserving filters preserve the edges and its information while blurring an image. In other words they are used to smooth an image, while reducing the edge blurring effects across the edge like halos, phantom etc. They are nonlinear in nature. Examples are bilateral filter, anisotropic diffusion filter, guided filter, trilateral filter etc. Hence these family of filters are very useful in reducing the noise in an image making it very demanding in computer vision and computational photography applications like denoising, video abstraction, demosaicing, optical-flow estimation, stereo match"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1503.07297","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1503.07297","created_at":"2026-05-18T02:20:21.537778+00:00"},{"alias_kind":"arxiv_version","alias_value":"1503.07297v1","created_at":"2026-05-18T02:20:21.537778+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1503.07297","created_at":"2026-05-18T02:20:21.537778+00:00"},{"alias_kind":"pith_short_12","alias_value":"N355KNDSDIB4","created_at":"2026-05-18T12:29:32.376354+00:00"},{"alias_kind":"pith_short_16","alias_value":"N355KNDSDIB4UCCO","created_at":"2026-05-18T12:29:32.376354+00:00"},{"alias_kind":"pith_short_8","alias_value":"N355KNDS","created_at":"2026-05-18T12:29:32.376354+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/N355KNDSDIB4UCCO2OZHJX2ASO","json":"https://pith.science/pith/N355KNDSDIB4UCCO2OZHJX2ASO.json","graph_json":"https://pith.science/api/pith-number/N355KNDSDIB4UCCO2OZHJX2ASO/graph.json","events_json":"https://pith.science/api/pith-number/N355KNDSDIB4UCCO2OZHJX2ASO/events.json","paper":"https://pith.science/paper/N355KNDS"},"agent_actions":{"view_html":"https://pith.science/pith/N355KNDSDIB4UCCO2OZHJX2ASO","download_json":"https://pith.science/pith/N355KNDSDIB4UCCO2OZHJX2ASO.json","view_paper":"https://pith.science/paper/N355KNDS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1503.07297&json=true","fetch_graph":"https://pith.science/api/pith-number/N355KNDSDIB4UCCO2OZHJX2ASO/graph.json","fetch_events":"https://pith.science/api/pith-number/N355KNDSDIB4UCCO2OZHJX2ASO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/N355KNDSDIB4UCCO2OZHJX2ASO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/N355KNDSDIB4UCCO2OZHJX2ASO/action/storage_attestation","attest_author":"https://pith.science/pith/N355KNDSDIB4UCCO2OZHJX2ASO/action/author_attestation","sign_citation":"https://pith.science/pith/N355KNDSDIB4UCCO2OZHJX2ASO/action/citation_signature","submit_replication":"https://pith.science/pith/N355KNDSDIB4UCCO2OZHJX2ASO/action/replication_record"}},"created_at":"2026-05-18T02:20:21.537778+00:00","updated_at":"2026-05-18T02:20:21.537778+00:00"}