{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:VMCNCRSHFJ7ZNHSOLMOHCAHFCF","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":"44641de4eab1f3c7389d046c5f515402f2ceb6237eb2e02ba8a825bb03e6be34","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2016-12-25T17:01:25Z","title_canon_sha256":"cc6b82d48f9f00ad18aba31f0926c6eb3f46dc188cf3a58bbf8193f35b25f13c"},"schema_version":"1.0","source":{"id":"1612.08656","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1612.08656","created_at":"2026-05-17T23:44:00Z"},{"alias_kind":"arxiv_version","alias_value":"1612.08656v1","created_at":"2026-05-17T23:44:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.08656","created_at":"2026-05-17T23:44:00Z"},{"alias_kind":"pith_short_12","alias_value":"VMCNCRSHFJ7Z","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_16","alias_value":"VMCNCRSHFJ7ZNHSO","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_8","alias_value":"VMCNCRSH","created_at":"2026-05-18T12:30:48Z"}],"graph_snapshots":[{"event_id":"sha256:fd17066d807f578ebeb730e4d7e07fd206d3a7739fd3d95191956584ba258078","target":"graph","created_at":"2026-05-17T23:44:00Z","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":"Phaseless diffraction measurements recorded by a CCD detector are often affected by Poisson noise. In this paper, we propose a dictionary learning model by employing patches based sparsity to denoise Poisson phaseless measurement. The model consists of three terms: (i) A representation term by an orthogonal dictionary, (ii) an $L^0$ pseudo norm of coefficient matrix, and (iii) a Kullback-Leibler divergence to fit phaseless Poisson data. Fast Alternating Minimization Method (AMM) and Proximal Alternating Linearized Minimization (PALM) are adopted to solve the established model with convergence ","authors_text":"Huibin Chang, Stefano Marchesini","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2016-12-25T17:01:25Z","title":"Denoising Poisson Phaseless Measurements via Orthogonal Dictionary Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.08656","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:f173c67917c81823d4579aa06389b65cde13db7d5c88f63f8562256deb7f1e36","target":"record","created_at":"2026-05-17T23:44:00Z","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":"44641de4eab1f3c7389d046c5f515402f2ceb6237eb2e02ba8a825bb03e6be34","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2016-12-25T17:01:25Z","title_canon_sha256":"cc6b82d48f9f00ad18aba31f0926c6eb3f46dc188cf3a58bbf8193f35b25f13c"},"schema_version":"1.0","source":{"id":"1612.08656","kind":"arxiv","version":1}},"canonical_sha256":"ab04d146472a7f969e4e5b1c7100e5116ec5444e13f8834be133339972e76398","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ab04d146472a7f969e4e5b1c7100e5116ec5444e13f8834be133339972e76398","first_computed_at":"2026-05-17T23:44:00.275658Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:44:00.275658Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vqCPboW2aWoPQzsuV2ROTE+tX8s31GBAAKNC0mvPAC3lTZeoHEY3c7HVPOhCY2LXDKSRqPbx3qX2qvD0TBtRDA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:44:00.276264Z","signed_message":"canonical_sha256_bytes"},"source_id":"1612.08656","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f173c67917c81823d4579aa06389b65cde13db7d5c88f63f8562256deb7f1e36","sha256:fd17066d807f578ebeb730e4d7e07fd206d3a7739fd3d95191956584ba258078"],"state_sha256":"362f8bff0733d5e562454542aeae7d8d12e2930d7c06629ce1bdbd210a7832f9"}