{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:WFLU5A6KCYHPK3BUQBKNQTCEHL","short_pith_number":"pith:WFLU5A6K","canonical_record":{"source":{"id":"1611.07752","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-11-23T11:53:15Z","cross_cats_sorted":[],"title_canon_sha256":"7a92052bc4f5d641ab464c95cfcc9bf3fe58764822835988f4012f62b36d723a","abstract_canon_sha256":"755d1d7fc9ae5945a9f2cce9ba27265c4c56032a7a4535417b246fc5f548cc96"},"schema_version":"1.0"},"canonical_sha256":"b1574e83ca160ef56c348054d84c443aed6a9f3d3b0bc1b2a9c999bd847d8aa5","source":{"kind":"arxiv","id":"1611.07752","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.07752","created_at":"2026-05-18T00:36:39Z"},{"alias_kind":"arxiv_version","alias_value":"1611.07752v2","created_at":"2026-05-18T00:36:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.07752","created_at":"2026-05-18T00:36:39Z"},{"alias_kind":"pith_short_12","alias_value":"WFLU5A6KCYHP","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_16","alias_value":"WFLU5A6KCYHPK3BU","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_8","alias_value":"WFLU5A6K","created_at":"2026-05-18T12:30:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:WFLU5A6KCYHPK3BUQBKNQTCEHL","target":"record","payload":{"canonical_record":{"source":{"id":"1611.07752","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-11-23T11:53:15Z","cross_cats_sorted":[],"title_canon_sha256":"7a92052bc4f5d641ab464c95cfcc9bf3fe58764822835988f4012f62b36d723a","abstract_canon_sha256":"755d1d7fc9ae5945a9f2cce9ba27265c4c56032a7a4535417b246fc5f548cc96"},"schema_version":"1.0"},"canonical_sha256":"b1574e83ca160ef56c348054d84c443aed6a9f3d3b0bc1b2a9c999bd847d8aa5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:36:39.131024Z","signature_b64":"m4tWqCQNq9ab1EJDpyde3yLRnVbWjLFMJS74D75F8LMLT9+z5CN9HcNqRGYOp2u6/vEOBBa6kxN/PiJ/cI6cDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b1574e83ca160ef56c348054d84c443aed6a9f3d3b0bc1b2a9c999bd847d8aa5","last_reissued_at":"2026-05-18T00:36:39.130516Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:36:39.130516Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1611.07752","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:36:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZL/93II6jlgbZt29oA1I/nCM+NpkF2SPMLOWERQmavcSpuX9EFXRt22r5f+4mT2VAsiPkgMDfRITXzLg9GF1Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T15:46:19.483006Z"},"content_sha256":"ef8561ff078753b60c8ee355fd7a541f1e12ace9e159bdc1dbac4d136885bdbf","schema_version":"1.0","event_id":"sha256:ef8561ff078753b60c8ee355fd7a541f1e12ace9e159bdc1dbac4d136885bdbf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:WFLU5A6KCYHPK3BUQBKNQTCEHL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Convergence Analysis of MAP based Blur Kernel Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Seungyong Lee, Sunghyun Cho","submitted_at":"2016-11-23T11:53:15Z","abstract_excerpt":"One popular approach for blind deconvolution is to formulate a maximum a posteriori (MAP) problem with sparsity priors on the gradients of the latent image, and then alternatingly estimate the blur kernel and the latent image. While several successful MAP based methods have been proposed, there has been much controversy and confusion about their convergence, because sparsity priors have been shown to prefer blurry images to sharp natural images. In this paper, we revisit this problem and provide an analysis on the convergence of MAP based approaches. We first introduce a slight modification to"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.07752","kind":"arxiv","version":2},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:36:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mDw6MYkScbdoiUOpaGuH3SGEBC1WdATpw6ccXdA6RUFdD1PiC1eI/JWRU9I0K5Lhzi9CD/dlLIo/xKSoNUmPCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T15:46:19.483371Z"},"content_sha256":"b545a38d148e28cc82a5b28023a141d67c66d79cdbd06c88e0ab371c63bf1b00","schema_version":"1.0","event_id":"sha256:b545a38d148e28cc82a5b28023a141d67c66d79cdbd06c88e0ab371c63bf1b00"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WFLU5A6KCYHPK3BUQBKNQTCEHL/bundle.json","state_url":"https://pith.science/pith/WFLU5A6KCYHPK3BUQBKNQTCEHL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WFLU5A6KCYHPK3BUQBKNQTCEHL/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-30T15:46:19Z","links":{"resolver":"https://pith.science/pith/WFLU5A6KCYHPK3BUQBKNQTCEHL","bundle":"https://pith.science/pith/WFLU5A6KCYHPK3BUQBKNQTCEHL/bundle.json","state":"https://pith.science/pith/WFLU5A6KCYHPK3BUQBKNQTCEHL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WFLU5A6KCYHPK3BUQBKNQTCEHL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:WFLU5A6KCYHPK3BUQBKNQTCEHL","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":"755d1d7fc9ae5945a9f2cce9ba27265c4c56032a7a4535417b246fc5f548cc96","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-11-23T11:53:15Z","title_canon_sha256":"7a92052bc4f5d641ab464c95cfcc9bf3fe58764822835988f4012f62b36d723a"},"schema_version":"1.0","source":{"id":"1611.07752","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.07752","created_at":"2026-05-18T00:36:39Z"},{"alias_kind":"arxiv_version","alias_value":"1611.07752v2","created_at":"2026-05-18T00:36:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.07752","created_at":"2026-05-18T00:36:39Z"},{"alias_kind":"pith_short_12","alias_value":"WFLU5A6KCYHP","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_16","alias_value":"WFLU5A6KCYHPK3BU","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_8","alias_value":"WFLU5A6K","created_at":"2026-05-18T12:30:48Z"}],"graph_snapshots":[{"event_id":"sha256:b545a38d148e28cc82a5b28023a141d67c66d79cdbd06c88e0ab371c63bf1b00","target":"graph","created_at":"2026-05-18T00:36:39Z","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":"One popular approach for blind deconvolution is to formulate a maximum a posteriori (MAP) problem with sparsity priors on the gradients of the latent image, and then alternatingly estimate the blur kernel and the latent image. While several successful MAP based methods have been proposed, there has been much controversy and confusion about their convergence, because sparsity priors have been shown to prefer blurry images to sharp natural images. In this paper, we revisit this problem and provide an analysis on the convergence of MAP based approaches. We first introduce a slight modification to","authors_text":"Seungyong Lee, Sunghyun Cho","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-11-23T11:53:15Z","title":"Convergence Analysis of MAP based Blur Kernel Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.07752","kind":"arxiv","version":2},"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:ef8561ff078753b60c8ee355fd7a541f1e12ace9e159bdc1dbac4d136885bdbf","target":"record","created_at":"2026-05-18T00:36:39Z","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":"755d1d7fc9ae5945a9f2cce9ba27265c4c56032a7a4535417b246fc5f548cc96","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-11-23T11:53:15Z","title_canon_sha256":"7a92052bc4f5d641ab464c95cfcc9bf3fe58764822835988f4012f62b36d723a"},"schema_version":"1.0","source":{"id":"1611.07752","kind":"arxiv","version":2}},"canonical_sha256":"b1574e83ca160ef56c348054d84c443aed6a9f3d3b0bc1b2a9c999bd847d8aa5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b1574e83ca160ef56c348054d84c443aed6a9f3d3b0bc1b2a9c999bd847d8aa5","first_computed_at":"2026-05-18T00:36:39.130516Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:36:39.130516Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"m4tWqCQNq9ab1EJDpyde3yLRnVbWjLFMJS74D75F8LMLT9+z5CN9HcNqRGYOp2u6/vEOBBa6kxN/PiJ/cI6cDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:36:39.131024Z","signed_message":"canonical_sha256_bytes"},"source_id":"1611.07752","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ef8561ff078753b60c8ee355fd7a541f1e12ace9e159bdc1dbac4d136885bdbf","sha256:b545a38d148e28cc82a5b28023a141d67c66d79cdbd06c88e0ab371c63bf1b00"],"state_sha256":"a0748f109feaa79b5970da63b3d0fc36c72c1ad70064587344f7b5af4872b5c0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JYs77IaDZyRH2xFFd4DR8IlMnh/E7Bf5u+eecMKk+h2kw1ongj0iO7M9Ei7Ue5UtggDtME7dO5LRzeHbXJz4Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T15:46:19.485613Z","bundle_sha256":"2e32e39f187fbd798b15503a6b6f2e2be2e4677563f93a9aa6059c26b0fe1c28"}}