{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:36JBHC5UGQZFH6X6LLAU5RRD2G","short_pith_number":"pith:36JBHC5U","schema_version":"1.0","canonical_sha256":"df92138bb4343253fafe5ac14ec623d188664486c4384479c272bf2bb836644e","source":{"kind":"arxiv","id":"1707.09926","version":1},"attestation_state":"computed","paper":{"title":"A Framework for Super-Resolution of Scalable Video via Sparse Reconstruction of Residual Frames","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Besma Smida, Mohammad Hossein Moghaddam, Mohammad Javad Azizipour, Saeed Vahidian","submitted_at":"2017-07-31T15:47:47Z","abstract_excerpt":"This paper introduces a framework for super-resolution of scalable video based on compressive sensing and sparse representation of residual frames in reconnaissance and surveillance applications. We exploit efficient compressive sampling and sparse reconstruction algorithms to super-resolve the video sequence with respect to different compression rates. We use the sparsity of residual information in residual frames as the key point in devising our framework. Moreover, a controlling factor as the compressibility threshold to control the complexity-performance trade-off is defined. Numerical exp"},"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":"1707.09926","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-31T15:47:47Z","cross_cats_sorted":[],"title_canon_sha256":"4a7ba16d0e413567a375f671688ba230a15ca913b274791c397c78be6f53680f","abstract_canon_sha256":"40cd83725c013bcce7212c9a52b18acf6cd9d418068297237e31f3431e77923f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:39:07.745417Z","signature_b64":"NBNhDpyP/CV3r7TvlJT/IwsaByYSRx7fu6nhsoulRTbC0QysTgohWDpPUVlxgJySv6TgX9OzqqxGzb9gKGJTAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"df92138bb4343253fafe5ac14ec623d188664486c4384479c272bf2bb836644e","last_reissued_at":"2026-05-18T00:39:07.744715Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:39:07.744715Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Framework for Super-Resolution of Scalable Video via Sparse Reconstruction of Residual Frames","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Besma Smida, Mohammad Hossein Moghaddam, Mohammad Javad Azizipour, Saeed Vahidian","submitted_at":"2017-07-31T15:47:47Z","abstract_excerpt":"This paper introduces a framework for super-resolution of scalable video based on compressive sensing and sparse representation of residual frames in reconnaissance and surveillance applications. We exploit efficient compressive sampling and sparse reconstruction algorithms to super-resolve the video sequence with respect to different compression rates. We use the sparsity of residual information in residual frames as the key point in devising our framework. Moreover, a controlling factor as the compressibility threshold to control the complexity-performance trade-off is defined. Numerical exp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.09926","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":"1707.09926","created_at":"2026-05-18T00:39:07.744806+00:00"},{"alias_kind":"arxiv_version","alias_value":"1707.09926v1","created_at":"2026-05-18T00:39:07.744806+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.09926","created_at":"2026-05-18T00:39:07.744806+00:00"},{"alias_kind":"pith_short_12","alias_value":"36JBHC5UGQZF","created_at":"2026-05-18T12:30:58.224056+00:00"},{"alias_kind":"pith_short_16","alias_value":"36JBHC5UGQZFH6X6","created_at":"2026-05-18T12:30:58.224056+00:00"},{"alias_kind":"pith_short_8","alias_value":"36JBHC5U","created_at":"2026-05-18T12:30:58.224056+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/36JBHC5UGQZFH6X6LLAU5RRD2G","json":"https://pith.science/pith/36JBHC5UGQZFH6X6LLAU5RRD2G.json","graph_json":"https://pith.science/api/pith-number/36JBHC5UGQZFH6X6LLAU5RRD2G/graph.json","events_json":"https://pith.science/api/pith-number/36JBHC5UGQZFH6X6LLAU5RRD2G/events.json","paper":"https://pith.science/paper/36JBHC5U"},"agent_actions":{"view_html":"https://pith.science/pith/36JBHC5UGQZFH6X6LLAU5RRD2G","download_json":"https://pith.science/pith/36JBHC5UGQZFH6X6LLAU5RRD2G.json","view_paper":"https://pith.science/paper/36JBHC5U","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1707.09926&json=true","fetch_graph":"https://pith.science/api/pith-number/36JBHC5UGQZFH6X6LLAU5RRD2G/graph.json","fetch_events":"https://pith.science/api/pith-number/36JBHC5UGQZFH6X6LLAU5RRD2G/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/36JBHC5UGQZFH6X6LLAU5RRD2G/action/timestamp_anchor","attest_storage":"https://pith.science/pith/36JBHC5UGQZFH6X6LLAU5RRD2G/action/storage_attestation","attest_author":"https://pith.science/pith/36JBHC5UGQZFH6X6LLAU5RRD2G/action/author_attestation","sign_citation":"https://pith.science/pith/36JBHC5UGQZFH6X6LLAU5RRD2G/action/citation_signature","submit_replication":"https://pith.science/pith/36JBHC5UGQZFH6X6LLAU5RRD2G/action/replication_record"}},"created_at":"2026-05-18T00:39:07.744806+00:00","updated_at":"2026-05-18T00:39:07.744806+00:00"}