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
17
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
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
610
iOS 18 がやってきた!
kno3a87
1
180
おうちハッカソン #2
kno3a87
0
120
ミクアカ成果報告会
kno3a87
0
24
SXSW2021
kno3a87
0
39
ミクアカ中間発表会
kno3a87
0
14
大学院進学ガイダンス
kno3a87
0
76
内定者自己紹介LT
kno3a87
0
69
画像処理論セミナー7-1,2
kno3a87
0
13
Other Decks in Education
See All in Education
自己紹介 / who-am-i
yasulab
PRO
2
4.6k
Казармы и гарнизоны
pnuslide
0
180
HCI Research Methods - Lecture 7 - Human-Computer Interaction (1023841ANR)
signer
PRO
0
850
書を持って、自転車で町へ出よう
yuritaco
0
140
付箋を使ったカラオケでワイワイしましょう / Scrum Fest Okinawa 2024
bonbon0605
0
140
Informasi Program Coding Camp 2025 powered by DBS Foundation
codingcamp2025
0
160
Sähköiset kyselyt, kokeet ja arviointi
matleenalaakso
1
18k
MySmartSTEAM2425
cbtlibrary
0
120
Tips for the Presentation - Lecture 2 - Advanced Topics in Big Data (4023256FNR)
signer
PRO
0
200
AI 時代軟體工程師的持續升級
mosky
1
2.1k
Power Automate+ChatGPTを使ってエンジニア教育を改善してみた #RPALT
masakiokuda
0
140
Medidas en informática
irocho
0
1.1k
Featured
See All Featured
Rails Girls Zürich Keynote
gr2m
94
13k
Docker and Python
trallard
44
3.3k
Making Projects Easy
brettharned
116
6k
KATA
mclloyd
29
14k
How STYLIGHT went responsive
nonsquared
98
5.4k
Fireside Chat
paigeccino
34
3.2k
Building Adaptive Systems
keathley
40
2.4k
Understanding Cognitive Biases in Performance Measurement
bluesmoon
27
1.6k
RailsConf 2023
tenderlove
29
1k
VelocityConf: Rendering Performance Case Studies
addyosmani
328
24k
The Success of Rails: Ensuring Growth for the Next 100 Years
eileencodes
44
7k
Designing Dashboards & Data Visualisations in Web Apps
destraynor
231
53k
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