{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2011:CHMU67EZ4DSLENRFTAXI7R6O6Q","short_pith_number":"pith:CHMU67EZ","schema_version":"1.0","canonical_sha256":"11d94f7c99e0e4b23625982e8fc7cef40e27103b9e3a980b1e2863b8903ed0de","source":{"kind":"arxiv","id":"1108.4098","version":1},"attestation_state":"computed","paper":{"title":"Multisensor Images Fusion Based on Feature-Level","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ali A. Al-Zaky, Firouz Abdullah Al-Wassai, N.V. Kalyankar","submitted_at":"2011-08-20T07:43:46Z","abstract_excerpt":"Until now, of highest relevance for remote sensing data processing and analysis have been techniques for pixel level image fusion. So, This paper attempts to undertake the study of Feature-Level based image fusion. For this purpose, feature based fusion techniques, which are usually based on empirical or heuristic rules, are employed. Hence, in this paper we consider feature extraction (FE) for fusion. It aims at finding a transformation of the original space that would produce such new features, which preserve or improve as much as possible. This study introduces three different types of Imag"},"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":"1108.4098","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2011-08-20T07:43:46Z","cross_cats_sorted":[],"title_canon_sha256":"d39a00c13b25b02a7e19d42789b4f7cbe4f6ad7637673f7020112f97fdeaad01","abstract_canon_sha256":"761f684698c0c566ac9f96be02bd695c9085d37473e8f9402aecb7359fb6a1c6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:45:31.960211Z","signature_b64":"LS7AjeyQ9/813S03NHuGG0P9+r6xQ5WYWLiYKsvj9B7eQpHNGcXeKhMEZgWtKBP7z2WihW1o15etDX5clQ8JDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"11d94f7c99e0e4b23625982e8fc7cef40e27103b9e3a980b1e2863b8903ed0de","last_reissued_at":"2026-05-18T03:45:31.959608Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:45:31.959608Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multisensor Images Fusion Based on Feature-Level","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ali A. Al-Zaky, Firouz Abdullah Al-Wassai, N.V. Kalyankar","submitted_at":"2011-08-20T07:43:46Z","abstract_excerpt":"Until now, of highest relevance for remote sensing data processing and analysis have been techniques for pixel level image fusion. So, This paper attempts to undertake the study of Feature-Level based image fusion. For this purpose, feature based fusion techniques, which are usually based on empirical or heuristic rules, are employed. Hence, in this paper we consider feature extraction (FE) for fusion. It aims at finding a transformation of the original space that would produce such new features, which preserve or improve as much as possible. This study introduces three different types of Imag"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1108.4098","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":"1108.4098","created_at":"2026-05-18T03:45:31.959693+00:00"},{"alias_kind":"arxiv_version","alias_value":"1108.4098v1","created_at":"2026-05-18T03:45:31.959693+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1108.4098","created_at":"2026-05-18T03:45:31.959693+00:00"},{"alias_kind":"pith_short_12","alias_value":"CHMU67EZ4DSL","created_at":"2026-05-18T12:26:26.731475+00:00"},{"alias_kind":"pith_short_16","alias_value":"CHMU67EZ4DSLENRF","created_at":"2026-05-18T12:26:26.731475+00:00"},{"alias_kind":"pith_short_8","alias_value":"CHMU67EZ","created_at":"2026-05-18T12:26:26.731475+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/CHMU67EZ4DSLENRFTAXI7R6O6Q","json":"https://pith.science/pith/CHMU67EZ4DSLENRFTAXI7R6O6Q.json","graph_json":"https://pith.science/api/pith-number/CHMU67EZ4DSLENRFTAXI7R6O6Q/graph.json","events_json":"https://pith.science/api/pith-number/CHMU67EZ4DSLENRFTAXI7R6O6Q/events.json","paper":"https://pith.science/paper/CHMU67EZ"},"agent_actions":{"view_html":"https://pith.science/pith/CHMU67EZ4DSLENRFTAXI7R6O6Q","download_json":"https://pith.science/pith/CHMU67EZ4DSLENRFTAXI7R6O6Q.json","view_paper":"https://pith.science/paper/CHMU67EZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1108.4098&json=true","fetch_graph":"https://pith.science/api/pith-number/CHMU67EZ4DSLENRFTAXI7R6O6Q/graph.json","fetch_events":"https://pith.science/api/pith-number/CHMU67EZ4DSLENRFTAXI7R6O6Q/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CHMU67EZ4DSLENRFTAXI7R6O6Q/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CHMU67EZ4DSLENRFTAXI7R6O6Q/action/storage_attestation","attest_author":"https://pith.science/pith/CHMU67EZ4DSLENRFTAXI7R6O6Q/action/author_attestation","sign_citation":"https://pith.science/pith/CHMU67EZ4DSLENRFTAXI7R6O6Q/action/citation_signature","submit_replication":"https://pith.science/pith/CHMU67EZ4DSLENRFTAXI7R6O6Q/action/replication_record"}},"created_at":"2026-05-18T03:45:31.959693+00:00","updated_at":"2026-05-18T03:45:31.959693+00:00"}