options(warn=-1) # turns off warnings, to turn on: "options(warn=0)"


library(imager)
library(png)

for (f in list.files(path="nt_toolbox/toolbox_general/", pattern="*.R")) {
    source(paste("nt_toolbox/toolbox_general/", f, sep=""))
}

for (f in list.files(path="nt_toolbox/toolbox_signal/", pattern="*.R")) {
    source(paste("nt_toolbox/toolbox_signal/", f, sep=""))
}
options(repr.plot.width=3.5, repr.plot.height=3.5)

n <- 512
f <- rescale(load_image("nt_toolbox/data/lena.png", n))

imageplot(f)

fF <- fft(f)/n

imageplot(log(1e-5 + abs(fftshift(as.matrix(fF)))))

T <- .3
c <- fF * (abs(fF) > T)

fM <- Re( (fft(c, inverse=TRUE)/length(c))*n )

imageplot(clamp(fM))

options(repr.plot.width=7, repr.plot.height=3.5)

source("nt_solutions/coding_1_approximation/exo1.R")

## Insert your code here.

options(repr.plot.width=3.5, repr.plot.height=3.5)

source("nt_solutions/coding_1_approximation/exo2.R")

## Insert your code here.

options(repr.plot.width=3.5, repr.plot.height=3.5)

source("nt_solutions/coding_1_approximation/exo3.R")

## Insert your code here.

Jmin <- 1

h <- compute_wavelet_filter("Daubechies",10)

fW <- perform_wavortho_transf(f, Jmin, + 1, h)

plot_wavelet(fW, Jmin)
title(main='Wavelet coefficients')

options(repr.plot.width=7, repr.plot.height=3.5)

source("nt_solutions/coding_1_approximation/exo4.R")

## Insert your code here.

options(repr.plot.width=4, repr.plot.height=4)

source("nt_solutions/coding_1_approximation/exo5.R")

## Insert your code here

dct2 <- function(f){
    return( t(dct_2d(t(dct_2d(as.matrix(f))))) )
}

idct2 <- function(f){
    return( t(dct_2d(t(dct_2d(as.matrix(f),inverted=T)), inverted=T)) )
}

fC <- dct2(f)

imageplot(log(1e-5 + abs(fC)))

options(repr.plot.width=7, repr.plot.height=3.5)

source("nt_solutions/coding_1_approximation/exo6.R")

## Insert your code here.

options(repr.plot.width=4, repr.plot.height=4)

source("nt_solutions/coding_1_approximation/exo7.R")

## Insert your code here.

w <- 16

fL <- matrix(rep(0, length=n*n), c(n, n))

i <- 5
j <- 7

P <- as.matrix(f)[((i-1)*w):(i*w-1), ((j-1)*w):(j*w-1)]

fL[((i-1)*w):(i*w-1), ((j-1)*w):(j*w-1)] = dct2(P)

options(repr.plot.width=7, repr.plot.height=3.5)

imageplot(P, 'Patch', c(1, 2, 1))
imageplot(dct2(P-mean(P)), 'DCT', c(1, 2, 2))

source("nt_solutions/coding_1_approximation/exo8.R")

## Insert your code here.

options(repr.plot.width=3.5, repr.plot.height=3.5)

imageplot(clip(abs(fL),0,.005*w*w))

source("nt_solutions/coding_1_approximation/exo9.R")

## Insert your code here.

options(repr.plot.width=7, repr.plot.height=3.5)

source("nt_solutions/coding_1_approximation/exo10.R")

## Insert your code here.

options(repr.plot.width=4, repr.plot.height=4)

source("nt_solutions/coding_1_approximation/exo11.R")

## Insert your code here.

n <- 512
fList <- array(rep(0, length=n*n*4), c(n, n, 4))
fList[ ,  , 1] <- rescale(load_image("nt_toolbox/data/regular3.png", n))
fList[ ,  , 2] <- rescale(load_image("nt_toolbox/data/phantom.png", n))
fList[ ,  , 3] <- rescale(load_image("nt_toolbox/data/lena.png", n))
fList[ ,  , 4] <- rescale(load_image("nt_toolbox/data/mandrill.png", n))

options(repr.plot.width=7, repr.plot.height=7)

for (i in 1:4){
    imageplot(fList[ , , i], '', c(2,2,i))
}

options(repr.plot.width=4, repr.plot.height=4)

source("nt_solutions/coding_1_approximation/exo12.R")

## Insert your code here.
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