Procesarea Imaginilor
Curs 7:
Convolutie. Transformata Fourier
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Convolutie
Notiuni preliminarii Imagine continua := functie continua de 2 variabile independente
Exemple: u(x, y); v(x, y); f(x, y)
Functie 2D separabila:
f(x,y)=f1(x)f2(y)
Imagine discreta (digitala) := secventa 2D (bidmensionala) de numere reale/intregi
Exemple: um,n ; v(m, n)
Notatii:
i,j,k,l,m,n indici intregi folositi in matrice, vectori:
1j
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Convolutie
Functia Dirac (impuls unitar Aria = 1)
Functia Dirac 2D (continua):
d(x,y) =d(x)d(y)
Functia discreta Kronecker:
d(m,n) =d(m)d(n)
Sistem
H
Sistem liniar (principiul superpozitiei liniare):
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Convolutie
Iesirea unui sistem liniar
Unde: Este raspunsul la impuls al sistemului iesirea sistemului H in punctul/locatia (m,n) atunci cand la intrare se aplica functia impuls unitar (Kronecker) la locatia (m,n).
H
Dc. y(m,n), x(m,n) >0 (ex: imagini), atunci h s.n. Points Spread Function (PSF)
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Convolutie
Regiune suport a raspunsului la impuls := cea mai mica regiune din planul (m,n) cu proprietatea ca in afara acestei regiuni raspunsul la impuls (h) este nul.
Sisteme FIR sisteme a caror raspuns la impuls au o regiune suport finita
Sisteme IIR sisteme a caror raspuns la impuls au o regiune suport infinita
Sistem invariant la translatie := sistem pt. care o translatie a intrarii va determina o translatie corespunzatoare a iesirii
forma raspunsului la impuls nu se schimba odata cu deplasarea impulsului in planul (m,n)
Convolutia intarii cu raspunsul la impuls:
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Convolutie
Convolutie 1D
Convolutie 2D
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Operaia de convoluie n domeniul spaial
Operaia de convoluie implic folosirea unei mti/nucleu de convoluie H (de obicei de form simetric de dimensiune wxw, cu w=2k+1) care se aplic peste imaginea surs:
SD IHI
( , ) ( , ) ( , ) , 0... 1, 0... 1k k
D Si k j k
I x y H i j I x i y j x Height y Width
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Convolutie Exemplu: filtru pt. detectia muchiilor verticale (calculeaza derivata imaginii pe directia x)
ImgSrc (i,j) ImgDst(i,j) =GX*ImgSrc (i,j)
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Transformata Fourier [1]
Notiuni preliminarii
Functie periodica serii Fourier (suma sin si cos de frecvente diferite)
Functie integrala (arie) finita trasnformata Fourier (inetgrala / suma de sin si cos)
Transformata Fourier (1D)
)sin()cos( xjxe jx
Transformata Fourier inversa (1D)
Se poate reface functia initiala plecand de la functia transformata !!!
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Transformata Fourier [1]
Transformata Fourier (2D):
Transformata Fourier discreta - DFT (1D):
u = 0, 1, 2, .. M-1 (domeniu de frecvente)
x = 0, 1, 2, .. M-1
F(0)= .. , F(1)= .. , , F(M-1)= .. (componente de frecvanta)
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Transformata Fourier [1]
Caracteruistici ale DFT
F(u) exprimata in coordonate polare:
Magnitudine (spectru) image enhancement
Faza (spectru de faza / unghi de faza)
Spectru de putere (densitate spectrala)
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Transformata Fourier [1]
Transformata Fourier discreta DFT (2D)
u = 0, 1, 2, .. M-1, v = 0, 1, 2, .. N-1 (coordonate/variabile de frecventa)
x = 0, 1, 2, .. M-1, y = 0, 1, 2, .. N-1 (coordonate/variabile spatiale)
Spectru:
Faza:
Spectru de putere:
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Transformata Fourier [1]
Shift-area transformatei Fourier:
M/2
N/2 F(0,0)
Componenta continua a spectrului:
intensitatea medie a imaginii
Pt. Imagini (f R):
Relatiile dintre esantioanele spatiale si frecventiale ale imaginii:
Spectru Fourier F(u,v) centrat
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Transformata Fourier [1]
Exemple de reprezentare a DFT
log(1+|F(u,v)|)
log(1+|F(u,v)|) F(u,v)
Pentru marirea contrastului zonelor intunecate din spectru se foloseste transformata log (pt. vizualizare mai buna)
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Transformata Fourier
Original log(|F(u,v)|) f(u,v)
Transformata directa
Transformata inversa
f(u,v)=0 (se ignora faza) |A(u,v)|=0 (se ignora amplitudinea)
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Transformata Fourier [1]
Filtrarea imaginilor in domeniul frecventelor
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Transformata Fourier [1]
Filtrarea imaginilor in domeniul frecventelor exemple:
Negativul imaginii:
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Transformata Fourier [1]
Filtrarea imaginilor in domeniul frecventelor exemple:
FTJ
FTS
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Transformata Fourier [1]
Filtrarea imaginilor in domeniul frecventelor exemple:
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Transformata Fourier [1]
Filtrarea imaginilor in domeniul frecventelor exemple: FTJ
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Transformata Fourier [1]
Filtrarea imaginilor in domeniul frecventelor exemple: FTJ ideal
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Transformata Fourier [1]
Filtrarea imaginilor in domeniul frecventelor exemple: FTJ Gausian
Technical University of Cluj Napoca
Computer Science Department IMAGE PROCESSING
Referinte
[1] R.C.Gonzales, R.E.Woods, "Digital Image Processing, 2-nd Edition", Prentice Hall, 2002, pp 147-177
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