Pith Number

pith:2CPJNUDT

pith:2026:2CPJNUDTIXSMFD4X25P6TL5PKO

not attested not anchored not stored refs resolved

HIR-ALIGN: Enhancing Hyperspectral Image Restoration via Diffusion-Based Data Generation

Deyu Meng, Heng Zhao, Li Pang, Xiangyong Cao, Yijia Zhang

Diffusion-generated synthetic HSIs allow finetuning of restoration models to match target domains without clean references

arxiv:2605.13581 v1 · 2026-05-13 · cs.CV

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\pithnumber{2CPJNUDTIXSMFD4X25P6TL5PKO}

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3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

augmentation-based finetuning can achieve lower target-domain restoration risk by jointly improving target distribution coverage and controlling spectral bias

C2weakest assumption

The proxy HSIs produced by off-the-shelf restoration models are semantics-preserving approximations of clean target-domain images, and the diffusion-generated RGBs can be accurately aligned to proxies via warp-based spectral transfer without introducing new biases.

C3one line summary

HIR-ALIGN augments limited target data for hyperspectral restoration by creating proxy clean images, synthesizing aligned HSIs with blur-robust diffusion and warp-based transfer, then finetuning models to lower target-domain risk.

References

69 extracted · 69 resolved · 5 Pith anchors

[1] Coupled segmentation and denoising/deblurring models for hyperspectral material identification, 2012

[2] Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumi- nation and atmospheric conditions, 1999

[3] Hyperspectral image dataset for benchmarking on salient object detection, 2018

[4] Material based salient object detection from hyperspectral images, 2018

[5] Object detection in hyperspectral images, 2021

Receipt and verification

First computed	2026-05-18T02:44:23.231656Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

d09e96d07345e4c28f97d75fe9afaf538cad2b6c3c1c15247706d12f01fc62bd

Aliases

arxiv: 2605.13581 · arxiv_version: 2605.13581v1 · doi: 10.48550/arxiv.2605.13581 · pith_short_12: 2CPJNUDTIXSM · pith_short_16: 2CPJNUDTIXSMFD4X · pith_short_8: 2CPJNUDT

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/2CPJNUDTIXSMFD4X25P6TL5PKO \
  | 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: d09e96d07345e4c28f97d75fe9afaf538cad2b6c3c1c15247706d12f01fc62bd

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "3b4ca972485c694eaeb37ff1120152fd8d394b548298b00d2137319cf4dcab1b",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-13T14:14:13Z",
    "title_canon_sha256": "d0a02f4169f49481437d30264f936993e8ba2cf008990609f039ce3faead1c06"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13581",
    "kind": "arxiv",
    "version": 1
  }
}