PaperActive

Mi-Ripple: Restoring Images Degraded by Iterative AI Editing

Updated 42 min ago · first seen 11 Sept 2026

paper_01M294H20P828QX5F86ZEB9J7T

Published: 11 Sept 2026; T1 · 51 min ago
arXiv: 2609.11317; T1 · 51 min ago
Category: cs.CV; T1 · 51 min ago

Abstract

Iterative reference-conditioned image editing can introduce grid-like and granular textures, commonly described as digital ripple. We present Mi-Ripple, a diagnosis-guided restoration workflow that suppresses this digital ripple while protecting image structure. Mi-Ripple separates periodic lattice artifacts from content-entangled granular texture, then combines selective spectral notching, structure-aware smoothing, and cleaned-reference regeneration. This separation enables low-distortion filtering when artifacts are spectrally isolated and visual reconstruction when filtering would erase legitimate detail. Across fourteen notch-only executions, whole-image residual standard deviation is 0.08--0.44 in CIELAB lightness units. In a paired regeneration example, reference cleaning reduces output debris density by 45\%. Mi-Ripple links measurable artifact reduction to visibly cleaner generated images, rather than optimizing a spectral score alone.

Authors 3

Jiayin Chen, Yicheng Xu, Muting Wang

Specification

Official page: arxiv.org/abs/2609.11317
Source:arXiv (Atom API + RSS)T1observed 51 min agohigh
Arxiv announce type: new
Source:arXiv (Atom API + RSS)T1observed 51 min agohigh
arXiv id: 2609.11317
Source:arXiv (Atom API + RSS)T1observed 51 min agohigh
Categories: cs.CV
Source:arXiv (Atom API + RSS)T1observed 51 min agohigh
Github repo: miyang-ai/Mi-Ripple
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 44 min agomedium
Hf paper url: https://huggingface.co/papers/2609.11317
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 44 min agomedium
Github stars: 34
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 42 min agomedium
Hf comments: 2
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 42 min agomedium
Upvotes: 20
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 42 min agomedium
PDF: arxiv.org/pdf/2609.11317
Source:arXiv (Atom API + RSS)T1observed 51 min agohigh
Primary category: cs.CV
Source:arXiv (Atom API + RSS)T1observed 51 min agohigh
Published: 11 Sept 2026
Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

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Source tiers

T1T29 / 5

Freshest observation

42 min ago

Conflicts

2 flagged

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Claim history

16 claims · 14 properties2 conflicting

Official pageofficial_url1

Claim history for Official page
Value	Valid from → to	Status	Source	Confidence	Extractor
https://arxiv.org/abs/2609.11317	11 Sept 2026 21:03 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

Abstractabstract1

Claim history for Abstract
Value	Valid from → to	Status	Source	Confidence	Extractor
Iterative reference-conditioned image editing can introduce grid-like and granular textures, commonly described as digital ripple. We present Mi-Ripple, a diagnosis-guided restoration workflow that suppresses this digital ripple while protecting image structure. Mi-Ripple separates periodic lattice artifacts from content-entangled granular texture, then combines selective spectral notching, structure-aware smoothing, and cleaned-reference regeneration. This separation enables low-distortion filtering when artifacts are spectrally isolated and visual reconstruction when filtering would erase legitimate detail. Across fourteen notch-only executions, whole-image residual standard deviation is 0.08--0.44 in CIELAB lightness units. In a paired regeneration example, reference cleaning reduces output debris density by 45\%. Mi-Ripple links measurable artifact reduction to visibly cleaner generated images, rather than optimizing a spectral score alone.	11 Sept 2026 21:03 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

Arxiv announce typearxiv_announce_type1

Claim history for Arxiv announce type
Value	Valid from → to	Status	Source	Confidence	Extractor
new	11 Sept 2026 21:03 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

arXiv idarxiv_id1

Claim history for arXiv id
Value	Valid from → to	Status	Source	Confidence	Extractor
2609.11317	11 Sept 2026 21:03 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

Authorsauthors1

Claim history for Authors
Value	Valid from → to	Status	Source	Confidence	Extractor
Jiayin Chen, Yicheng Xu, Muting Wang	11 Sept 2026 21:03 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

Categoriescategories1

Claim history for Categories
Value	Valid from → to	Status	Source	Confidence	Extractor
cs.CV	11 Sept 2026 21:03 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

Github repogithub_repo1

Claim history for Github repo
Value	Valid from → to	Status	Source	Confidence	Extractor
miyang-ai/Mi-Ripple	11 Sept 2026 21:10 UTC → current	current	Hugging Face Hub (public pages, model cards, papers)T2	medium	deterministic

Hf paper urlhf_paper_url1

Claim history for Hf paper url
Value	Valid from → to	Status	Source	Confidence	Extractor
https://huggingface.co/papers/2609.11317	11 Sept 2026 21:10 UTC → current	current	Hugging Face Hub (public pages, model cards, papers)T2	medium	deterministic

Github starsmetric.github_stars1

Claim history for Github stars
Value	Valid from → to	Status	Source	Confidence	Extractor
34	11 Sept 2026 21:10 UTC → current	current	Hugging Face Hub (public pages, model cards, papers)T2	medium	deterministic

Hf commentsmetric.hf_comments1

Claim history for Hf comments
Value	Valid from → to	Status	Source	Confidence	Extractor
2	11 Sept 2026 21:10 UTC → current	current	Hugging Face Hub (public pages, model cards, papers)T2	medium	deterministic

Upvotesmetric.upvotes1

Claim history for Upvotes
Value	Valid from → to	Status	Source	Confidence	Extractor
20	11 Sept 2026 21:10 UTC → current	current	Hugging Face Hub (public pages, model cards, papers)T2	medium	deterministic

PDFpdf_url1

Claim history for PDF
Value	Valid from → to	Status	Source	Confidence	Extractor
https://arxiv.org/pdf/2609.11317	11 Sept 2026 21:03 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

Primary categoryprimary_category1

Claim history for Primary category
Value	Valid from → to	Status	Source	Confidence	Extractor
cs.CV	11 Sept 2026 21:03 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

Publishedpublished_at3conflicting claims

Claim history for Published
Value	Valid from → to	Status	Source	Confidence	Extractor
10 Sept 2026	11 Sept 2026 21:12 UTC → current	conflicting	Hugging Face Hub (public pages, model cards, papers)T2	medium	deterministic
10 Sept 2026	11 Sept 2026 21:10 UTC → current	conflicting	Hugging Face Hub (public pages, model cards, papers)T2	medium	deterministic
11 Sept 2026	11 Sept 2026 21:03 UTC → current	current	arXiv (Atom API + RSS)T1	conflicted	deterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

Source documents
Source	Document	Type	Tier	Last observed	Snapshots
arXiv (Atom API + RSS)	rss.arxiv.org/rss/cs.CV	feed	T1· Official	51 min ago	1
Hugging Face Hub (public pages, model cards, papers)	huggingface.co/papers	listing	T2· Quality secondary	42 min ago	2

Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.