Hugging Face Daily Papers · · 3 min read

Mi-Ripple: Restoring Images Degraded by Iterative AI Editing

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We investigate “digital ripples” in AI-generated images, showing how resampling introduces periodic artifacts and why they can reappear after cleanup during subsequent editing.</p>\n","updatedAt":"2026-09-11T09:09:34.627Z","author":{"_id":"69e1eb933ceb9605d4db2007","avatarUrl":"/avatars/d2899498627e36d573965d713ec87c89.svg","fullname":"Jiayin Chen","name":"cnbird","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.9349417686462402},"editors":["cnbird"],"editorAvatarUrls":["/avatars/d2899498627e36d573965d713ec87c89.svg"],"reactions":[],"isReport":false}},{"id":"6aa3c89639e94c1d942333fb","author":{"_id":"69e1eb933ceb9605d4db2007","avatarUrl":"/avatars/d2899498627e36d573965d713ec87c89.svg","fullname":"Jiayin Chen","name":"cnbird","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"isUserFollowing":false},"createdAt":"2026-09-11T09:23:34.000Z","type":"comment","data":{"edited":false,"hidden":false,"latest":{"raw":"Welcome to try our website https://lab.miyang.cn/ripple/","html":"<p>Welcome to try our website <a href=\"https://lab.miyang.cn/ripple/\" rel=\"nofollow\">https://lab.miyang.cn/ripple/</a></p>\n","updatedAt":"2026-09-11T09:23:34.323Z","author":{"_id":"69e1eb933ceb9605d4db2007","avatarUrl":"/avatars/d2899498627e36d573965d713ec87c89.svg","fullname":"Jiayin Chen","name":"cnbird","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.4036255478858948},"editors":["cnbird"],"editorAvatarUrls":["/avatars/d2899498627e36d573965d713ec87c89.svg"],"reactions":[],"isReport":false}}],"primaryEmailConfirmed":false,"paper":{"id":"2609.11317","authors":[{"_id":"6aa3967047a406da7901e7ff","user":{"_id":"69e1eb933ceb9605d4db2007","avatarUrl":"/avatars/d2899498627e36d573965d713ec87c89.svg","isPro":false,"fullname":"Jiayin Chen","user":"cnbird","type":"user","name":"cnbird"},"name":"Jiayin Chen","status":"claimed_verified","statusLastChangedAt":"2026-09-11T08:45:04.759Z","hidden":false},{"_id":"6aa3967047a406da7901e800","name":"Yicheng Xu","hidden":false},{"_id":"6aa3967047a406da7901e801","user":{"_id":"6a1ecd3fdc5908e8dd1d2fba","avatarUrl":"/avatars/c38bad66752804d41dace2df11b575d8.svg","isPro":false,"fullname":"muwing wang","user":"muwing","type":"user","name":"muwing"},"name":"Muting Wang","status":"claimed_verified","statusLastChangedAt":"2026-09-11T09:53:18.773Z","hidden":false}],"publishedAt":"2026-09-10T00:00:00.000Z","submittedOnDailyAt":"2026-09-11T00:00:00.000Z","title":"Mi-Ripple: Restoring Images Degraded by Iterative AI Editing","submittedOnDailyBy":{"_id":"69e1eb933ceb9605d4db2007","avatarUrl":"/avatars/d2899498627e36d573965d713ec87c89.svg","isPro":false,"fullname":"Jiayin Chen","user":"cnbird","type":"user","name":"cnbird"},"summary":"Iterative reference-conditioned image editing can introduce grid-like and granular textures, commonly described as digital ripple. 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Papers
arxiv:2609.11317

Mi-Ripple: Restoring Images Degraded by Iterative AI Editing

Published on Sep 10
· Submitted by
Jiayin Chen
on Sep 11

Abstract

Mi-Ripple reduces digital ripple artifacts in edited images by separating lattice artifacts from texture and applying targeted spectral filtering and reference cleaning.

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.

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Paper author Paper submitter about 5 hours ago

We investigate “digital ripples” in AI-generated images, showing how resampling introduces periodic artifacts and why they can reappear after cleanup during subsequent editing.

Paper author Paper submitter about 5 hours ago

Welcome to try our website https://lab.miyang.cn/ripple/

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