{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:KBVQ3JBFXNS7VRIF4CUC2ZQXX6","short_pith_number":"pith:KBVQ3JBF","schema_version":"1.0","canonical_sha256":"506b0da425bb65fac505e0a82d6617bf81d91f57ae567e2d6e35e75dd4ca8397","source":{"kind":"arxiv","id":"1906.08673","version":1},"attestation_state":"computed","paper":{"title":"Enhancement of Underwater Images with Statistical Model of Background Light and Optimization of Transmission Map","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MM"],"primary_cat":"eess.IV","authors_text":"Antonio Liotta, Cristian Perra, Dongmei Huang, Wei Song, Yan Wang","submitted_at":"2019-06-19T12:19:45Z","abstract_excerpt":"Underwater images often have severe quality degradation and distortion due to light absorption and scattering in the water medium. A hazed image formation model is widely used to restore the image quality. It depends on two optical parameters: the background light and the transmission map. Underwater images can also be enhanced by color and contrast correction from the perspective of image processing. In this paper, we propose an effective underwater image enhancement method for underwater images in composition of underwater image restoration and color correction. Firstly, a manually annotated"},"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":"1906.08673","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-19T12:19:45Z","cross_cats_sorted":["cs.MM"],"title_canon_sha256":"39c4616da65a4369178845fd37f164896c3f542de2ca0a759e1d1ec3ab4d71c4","abstract_canon_sha256":"983a4233fd80674f5724f3cb05a5568231db3e3a6a7e0595ca254f7f61616091"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:42:49.618797Z","signature_b64":"o9avDnfRKcH8HM51oB6NPSrdlgfyfV/fN900/i7AEUPBB7CfOoGPMesTHfoB/TtiKOx9dcfNo2on1z93bFqiDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"506b0da425bb65fac505e0a82d6617bf81d91f57ae567e2d6e35e75dd4ca8397","last_reissued_at":"2026-05-17T23:42:49.618135Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:42:49.618135Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Enhancement of Underwater Images with Statistical Model of Background Light and Optimization of Transmission Map","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MM"],"primary_cat":"eess.IV","authors_text":"Antonio Liotta, Cristian Perra, Dongmei Huang, Wei Song, Yan Wang","submitted_at":"2019-06-19T12:19:45Z","abstract_excerpt":"Underwater images often have severe quality degradation and distortion due to light absorption and scattering in the water medium. A hazed image formation model is widely used to restore the image quality. It depends on two optical parameters: the background light and the transmission map. Underwater images can also be enhanced by color and contrast correction from the perspective of image processing. In this paper, we propose an effective underwater image enhancement method for underwater images in composition of underwater image restoration and color correction. Firstly, a manually annotated"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.08673","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":"1906.08673","created_at":"2026-05-17T23:42:49.618216+00:00"},{"alias_kind":"arxiv_version","alias_value":"1906.08673v1","created_at":"2026-05-17T23:42:49.618216+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.08673","created_at":"2026-05-17T23:42:49.618216+00:00"},{"alias_kind":"pith_short_12","alias_value":"KBVQ3JBFXNS7","created_at":"2026-05-18T12:33:21.387695+00:00"},{"alias_kind":"pith_short_16","alias_value":"KBVQ3JBFXNS7VRIF","created_at":"2026-05-18T12:33:21.387695+00:00"},{"alias_kind":"pith_short_8","alias_value":"KBVQ3JBF","created_at":"2026-05-18T12:33:21.387695+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/KBVQ3JBFXNS7VRIF4CUC2ZQXX6","json":"https://pith.science/pith/KBVQ3JBFXNS7VRIF4CUC2ZQXX6.json","graph_json":"https://pith.science/api/pith-number/KBVQ3JBFXNS7VRIF4CUC2ZQXX6/graph.json","events_json":"https://pith.science/api/pith-number/KBVQ3JBFXNS7VRIF4CUC2ZQXX6/events.json","paper":"https://pith.science/paper/KBVQ3JBF"},"agent_actions":{"view_html":"https://pith.science/pith/KBVQ3JBFXNS7VRIF4CUC2ZQXX6","download_json":"https://pith.science/pith/KBVQ3JBFXNS7VRIF4CUC2ZQXX6.json","view_paper":"https://pith.science/paper/KBVQ3JBF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1906.08673&json=true","fetch_graph":"https://pith.science/api/pith-number/KBVQ3JBFXNS7VRIF4CUC2ZQXX6/graph.json","fetch_events":"https://pith.science/api/pith-number/KBVQ3JBFXNS7VRIF4CUC2ZQXX6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KBVQ3JBFXNS7VRIF4CUC2ZQXX6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KBVQ3JBFXNS7VRIF4CUC2ZQXX6/action/storage_attestation","attest_author":"https://pith.science/pith/KBVQ3JBFXNS7VRIF4CUC2ZQXX6/action/author_attestation","sign_citation":"https://pith.science/pith/KBVQ3JBFXNS7VRIF4CUC2ZQXX6/action/citation_signature","submit_replication":"https://pith.science/pith/KBVQ3JBFXNS7VRIF4CUC2ZQXX6/action/replication_record"}},"created_at":"2026-05-17T23:42:49.618216+00:00","updated_at":"2026-05-17T23:42:49.618216+00:00"}