Pith Number

pith:6XCWGOOP

pith:2026:6XCWGOOPCTEQHZBNYICWWOZP6E

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Uncertainty-aware Spatial-Frequency Registration and Fusion for Infrared and Visible Images

Haoyuan Xu, Jinyuan Liu, Jun Ma, Xingyuan Li, Xingyue Zhu, Yang Zou, Zhiying Jiang

SFRF uses uncertainty estimates and thermal consistency to prevent cumulative errors when registering and fusing unregistered infrared and visible images.

arxiv:2605.13049 v1 · 2026-05-13 · cs.CV

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4 Citations open

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Claims

C1strongest claim

SFRF incorporates uncertainty estimation and infrared thermal radiation distribution consistency into a unified pipeline to handle the error accumulation for robust registration and fusion across both spatial and frequency domains.

C2weakest assumption

That uncertainty estimates produced at each registration stage can be reliably used to prevent cumulative errors from contaminating the final fused image without introducing new artifacts or requiring extensive tuning.

C3one line summary

SFRF combines uncertainty-aware multi-scale registration with frequency-domain thermal consistency and dual-branch fusion to handle unregistered infrared-visible image pairs.

References

43 extracted · 43 resolved · 0 Pith anchors

[1] Unsupervised multi-modal im- age registration via geometry preserving image-to-image transla- tion 2020

[2] Refusion: Learning image fusion from reconstruction with learnable loss via meta-learning.International Journal of Com- puter Vision, pages 1–21, 2024

[3] Beauchemin and John L 1995

[4] Large displacement optical flow: descriptor matching in variational mo- tion estimation.IEEE transactions on pattern analysis and ma- chine intelligence, 33(3):500–513, 2010

[5] Optical flow constraints on deformable models with applications to face tracking.International Journal of Computer Vision, 38(2):99–127, 2000

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-18T03:08:59.370643Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

f5c56339cf14c903e42dc2056b3b2ff124c41990778d5b3b8e1c7c012eef99da

Aliases

arxiv: 2605.13049 · arxiv_version: 2605.13049v1 · doi: 10.48550/arxiv.2605.13049 · pith_short_12: 6XCWGOOPCTEQ · pith_short_16: 6XCWGOOPCTEQHZBN · pith_short_8: 6XCWGOOP

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/6XCWGOOPCTEQHZBNYICWWOZP6E \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: f5c56339cf14c903e42dc2056b3b2ff124c41990778d5b3b8e1c7c012eef99da

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "034d636cd433ece28165d556b00860a79338f5eeba309e27ff61a6c16926b8a8",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-13T06:12:46Z",
    "title_canon_sha256": "2a1c743aad3f0f166a19d2d3344a68c0ede573e1c3f56fe40fa96f9ca2e339b9"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13049",
    "kind": "arxiv",
    "version": 1
  }
}