Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
画像処理論セミナー7-1-3
Search
Kuno Ayana
July 02, 2020
Education
0
24
画像処理論セミナー7-1-3
Kuno Ayana
July 02, 2020
Tweet
Share
More Decks by Kuno Ayana
See All by Kuno Ayana
Dart 参戦!!静的型付き言語界の隠れた実力者
kno3a87
0
200
Flutterを言い訳にしない!アプリの使い心地改善テクニック5選🔥
kno3a87
3
720
iOS 18 がやってきた!
kno3a87
1
220
おうちハッカソン #2
kno3a87
0
130
ミクアカ成果報告会
kno3a87
0
34
SXSW2021
kno3a87
0
48
ミクアカ中間発表会
kno3a87
0
24
大学院進学ガイダンス
kno3a87
0
83
内定者自己紹介LT
kno3a87
0
80
Other Decks in Education
See All in Education
Alumnote inc. Company Deck
yukinumata
0
1.6k
ARアプリを活用した防災まち歩きデータ作成ハンズオン
nro2daisuke
0
150
Pythonパッケージ管理 [uv] 完全入門
mickey_kubo
22
21k
データ分析
takenawa
0
14k
生態系ウォーズ - ルールブック
yui_itoshima
1
240
Open Source Summit Japan 2025のボランティアをしませんか
kujiraitakahiro
0
800
自己紹介 / who-am-i
yasulab
PRO
3
5.4k
Pydantic(AI)とJSONの詳細解説
mickey_kubo
0
170
2025年度春学期 統計学 第12回 分布の平均を推測する ー 区間推定 (2025. 6. 26)
akiraasano
PRO
0
150
ビジネスモデル理解
takenawa
0
14k
2025年度春学期 統計学 第10回 分布の推測とは ー 標本調査,度数分布と確率分布 (2025. 6. 12)
akiraasano
PRO
0
210
(2025) L'origami, mieux que la règle et le compas
mansuy
0
130
Featured
See All Featured
The Art of Delivering Value - GDevCon NA Keynote
reverentgeek
15
1.6k
How to Create Impact in a Changing Tech Landscape [PerfNow 2023]
tammyeverts
53
2.9k
"I'm Feeling Lucky" - Building Great Search Experiences for Today's Users (#IAC19)
danielanewman
229
22k
No one is an island. Learnings from fostering a developers community.
thoeni
21
3.4k
The Cost Of JavaScript in 2023
addyosmani
53
8.8k
Optimising Largest Contentful Paint
csswizardry
37
3.4k
RailsConf & Balkan Ruby 2019: The Past, Present, and Future of Rails at GitHub
eileencodes
139
34k
Building Flexible Design Systems
yeseniaperezcruz
328
39k
Building a Modern Day E-commerce SEO Strategy
aleyda
43
7.5k
GraphQLとの向き合い方2022年版
quramy
49
14k
Writing Fast Ruby
sferik
628
62k
Scaling GitHub
holman
462
140k
Transcript
,VOP"ZBOB σΟδλϧը૾ॲཧ ٯϑΟϧλɾΟʔφϑΟϧλʹΑΔը૾෮ݩ
લճͷ෮़ɿ΅͚ɾͿΕͱ ࣍ݩσϧλؔ δ(x, y) ྼԽը૾ g(x, y) ݪը૾ f(x, y)
લճͷ෮़ɿ֦͕ΓؔͷϞσϧԽ ΅͚ͷ֦͕ΓؔˠΨεͱۙࣅ ͿΕͷ֦͕ΓؔˠͿΕͷํВʹͷΈ෯XʹҰ࣍ݩͰ͕͍ͬͯΔؔͱۙࣅ
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ g(x, y) = f(x, y) * h(x, y) ྼԽը૾
ݪը૾ ֦͕Γؔ ֦͕Γ͕ؔطͷ߹ ٯϑΟϧλΛྼԽը૾ʹదԠ͢Δ͜ͱͰݪը૾͕ٻ·Δ
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ g(x, y) = f(x, y) * h(x, y) ྼԽը૾
ݪը૾ G(u, v) = F(u, v)H(u, v) ϑʔϦΤม 'ྼԽը૾ 'ݪը૾ ϑΟϧλ ֦͕Γؔ ֦͕Γ͕ؔطͷ߹ ٯϑΟϧλΛྼԽը૾ʹదԠ͢Δ͜ͱͰݪը૾͕ٻ·Δ
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ G(u, v) = F(u, v)H(u, v) 'ྼԽը૾ 'ݪը૾ ϑΟϧλ
֦͕Γ͕ؔطͷ߹ ٯϑΟϧλΛྼԽը૾ʹదԠ͢Δ͜ͱͰݪը૾͕ٻ·Δ
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ G(u, v) = F(u, v)H(u, v) 'ྼԽը૾ 'ݪը૾ ϑΟϧλ
֦͕Γ͕ؔطͷ߹ ٯϑΟϧλΛྼԽը૾ʹదԠ͢Δ͜ͱͰݪը૾͕ٻ·Δ K(u, v) K(u, v)
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ G(u, v) = F(u, v)H(u, v) 'ྼԽը૾ 'ݪը૾ ϑΟϧλ
1 H(u, v) ٯϑΟϧλ ֦͕Γ͕ؔطͷ߹ ٯϑΟϧλΛྼԽը૾ʹదԠ͢Δ͜ͱͰݪը૾͕ٻ·Δ 1 H(u, v)
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ G(u, v) = F(u, v)H(u, v) 'ྼԽը૾ 'ݪը૾ ϑΟϧλ
1 H(u, v) ٯϑΟϧλ ֦͕Γ͕ؔطͷ߹ ٯϑΟϧλΛྼԽը૾ʹదԠ͢Δ͜ͱͰݪը૾͕ٻ·Δ 1 H(u, v)
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ G(u, v) = F(u, v) 'ྼԽը૾ 'ݪը૾ ֦͕Γ͕ؔطͷ߹ ٯϑΟϧλΛྼԽը૾ʹదԠ͢Δ͜ͱͰݪը૾͕ٻ·Δ
1 H(u, v)
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ G(u, v) = F(u, v) 'ྼԽը૾ 'ݪը૾ ֦͕Γ͕ؔطͷ߹ ٯϑΟϧλΛྼԽը૾ʹదԠ͢Δ͜ͱͰݪը૾͕ٻ·Δ
1 H(u, v)
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ G(u, v) = F(u, v) 'ྼԽը૾ 'ݪը૾ ϑʔϦΤٯม g(x,
y) = f(x, y) ྼԽը૾ ݪը૾ ֦͕Γ͕ؔطͷ߹ ٯϑΟϧλΛྼԽը૾ʹదԠ͢Δ͜ͱͰݪը૾͕ٻ·Δ 1 H(u, v)
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ G(u, v) = F(u, v)H(u, v) 'ྼԽը૾ 'ݪը૾ ϑΟϧλ
1 H(u, v) ٯϑΟϧλ ֦͕Γ͕ؔطͷ߹ ٯϑΟϧλΛྼԽը૾ʹదԠ͢Δ͜ͱͰݪը૾͕ٻ·Δ ͘͠ݶΓͳ͘ʹ͍ۙͩͬͨΒʁ
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ G(u, v) = F(u, v)H(u, v) 'ྼԽը૾ 'ݪը૾ ϑΟϧλ
1 H(u, v) ٯϑΟϧλ ֦͕Γ͕ؔطͷ߹ ٯϑΟϧλΛྼԽը૾ʹదԠ͢Δ͜ͱͰݪը૾͕ٻ·Δ ͘͠ݶΓͳ͘ʹ͍ۙͩͬͨΒʁ ൃࢄͯ͠͠·͏ʂ
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ G(u, v) = F(u, v)H(u, v) + N(u, v)
ൃࢄ͢ΔͱϊΠζ͕૿෯ͯ͠͠·͏ ˠ) V W ͕ʹ͍ۙͱ͖ʹൃࢄ͠ͳ͍ϑΟϧλΛߟ͑Δඞཁ͕͋Δ 'ϊΠζ
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ Kw (u, v) = 1 H(u, v) ෮ݩը૾ɹɹɹͱݪը૾ɹɹɹͷޡࠩΛ࠷খʹ͢ΔΑ͏ͳϑΟϧλ Kw
(u, v) ̂ f(x, y) f(x, y)
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ Kw (u, v) = 1 H(u, v) |H(u, v)|2
|H(u, v)|2 + |N(u, v)|2 /|F(u, v)|2 ෮ݩը૾ɹɹɹͱݪը૾ɹɹɹͷޡࠩΛ࠷খʹ͢ΔΑ͏ͳϑΟϧλ Kw (u, v) ̂ f(x, y) f(x, y)
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ Kw (u, v) = 1 H(u, v) |H(u, v)|2
|H(u, v)|2 + |N(u, v)|2 /|F(u, v)|2 ෮ݩը૾ɹɹɹͱݪը૾ɹɹɹͷޡࠩΛ࠷খʹ͢ΔΑ͏ͳϑΟϧλ Kw (u, v) ̂ f(x, y) f(x, y) ΟʔφϑΟϧλ
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ Kw (u, v) = 1 H(u, v) |H(u, v)|2
|H(u, v)|2 + |N(u, v)|2 /|F(u, v)|2 ෮ݩը૾ɹɹɹͱݪը૾ɹɹɹͷޡࠩΛ࠷খʹ͢ΔΑ͏ͳϑΟϧλ Kw (u, v) ̂ f(x, y) f(x, y) ϊΠζ͕ͷ߹
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ Kw (u, v) = 1 H(u, v) |H(u, v)|2
|H(u, v)|2 + |N(u, v)|2 /|F(u, v)|2 ෮ݩը૾ɹɹɹͱݪը૾ɹɹɹͷޡࠩΛ࠷খʹ͢ΔΑ͏ͳϑΟϧλ Kw (u, v) ̂ f(x, y) f(x, y) ϊΠζ͕ͷ߹ ͕͜͜ʹͳΔͷͰ ٯϑΟϧλͱಉ༷ʹΔ
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ Kw (u, v) = 1 H(u, v) |H(u, v)|2
|H(u, v)|2 + |N(u, v)|2 /|F(u, v)|2 ෮ݩը૾ɹɹɹͱݪը૾ɹɹɹͷޡࠩΛ࠷খʹ͢ΔΑ͏ͳϑΟϧλ Kw (u, v) ̂ f(x, y) f(x, y) ͍͍ͩͨϊΠζݪը૾ະ దͳఆϵΛஔ͘͜ͱ͕ଟ͍
ը૾Λ෮ݩ͢ΔۭؒϑΟϧλΛߟ͑Δ Kw (u, v) = 1 H(u, v) |H(u, v)|2
|H(u, v)|2 + Γ ෮ݩը૾ɹɹɹͱݪը૾ɹɹɹͷޡࠩΛ࠷খʹ͢ΔΑ͏ͳϑΟϧλ Kw (u, v) ̂ f(x, y) f(x, y)
ϵΛมԽͤ͞Δ Kw (u, v) = 1 H(u, v) |H(u, v)|2
|H(u, v)|2 + Γ ਤ
ϵΛมԽͤ͞Δ Kw (u, v) = 1 H(u, v) |H(u, v)|2
|H(u, v)|2 + Γ ਤ ൃࢄͯ͠͠·͍ըૉ͕ൃࢄ͍ͯ͠Δ θϩΛؚΜͰ͍ΔͨΊ
ϵΛมԽͤ͞Δ Kw (u, v) = 1 H(u, v) |H(u, v)|2
|H(u, v)|2 + Γ ਤ ൃࢄͯ͠͠·͍ըૉ͕ൃࢄ͍ͯ͠Δ θϩΛؚΜͰ͍ΔͨΊ ൃࢄ͍ͯ͠ͳ͍
ϵΛมԽͤ͞Δ Kw (u, v) = 1 H(u, v) |H(u, v)|2
|H(u, v)|2 + Γ ਤ
ϵΛมԽͤ͞Δ Kw (u, v) = 1 H(u, v) |H(u, v)|2
|H(u, v)|2 + Γ ਤ Ӷʹ෮ݩ͞ΕΔ ϊΠζ૿෯͢Δ ϊΠζ૿෯͞Εͳ͍ ΅͚ɾͿΕͷ෮ݩ͕͍
ϵΛมԽͤ͞Δ Kw (u, v) = 1 H(u, v) |H(u, v)|2
|H(u, v)|2 + Γ ਤ Ӷʹ෮ݩ͞ΕΔ ϊΠζ૿෯͢Δ ϊΠζ૿෯͞Εͳ͍ ΅͚ɾͿΕͷ෮ݩ͕͍ ϵ͕େ͖͘ͳΔͱ͕େ͖͘ͳΔͷͰ
ϵΛมԽͤ͞Δ Kw (u, v) = 1 H(u, v) |H(u, v)|2
|H(u, v)|2 + Γ ਤ Ӷʹ෮ݩ͞ΕΔ ϊΠζ૿෯͢Δ ϊΠζ૿෯͞Εͳ͍ ΅͚ɾͿΕͷ෮ݩ͕͍ ϵ͕େ͖͘ͳΔͱ͕େ͖͘ͳΔͷͰ ͜͜ͷ͕খ͘͞ͳͬͯ͋·ΓϑΟϧλ͕ޮ͔ͳ͘ͳΔ