8.1

'''
Napraviti demo sliku dimenzije 256x256 sa dva kvadrata u sredini (jedan u drugom) koji su sa nijansama 127 i 191. Postaviti pozadinu na 63. Prikazati njen histogram.

Na ovu sliku dodati AWGN šum varijanse 100 i srednje vrednosti 0. Prikazati rezultat i histogram nove slike. Odrediti vršni odnost signal-šum.
'''

import plotly.graph_objects as go
from plotly.subplots import make_subplots
import numpy as np
import plotly.express as px


img = np.full((256, 256), fill_value=63)
img[32:32+192,32:32+192] = 127
img[64:64+128,64:64+128] = 191
fig = px.imshow(img, color_continuous_scale='gray')
fig.show()


rng = np.random.default_rng()
noise_im = rng.standard_normal(size=img.shape)

fig = px.imshow(noise_im, color_continuous_scale='gray')
fig.show()

img_noisy = img + noise_im*np.sqrt(100) + 0 # varijansa i srednja vrednost
img_noisy[img_noisy > 255] = 255
img_noisy[img_noisy < 0] = 0
fig = px.imshow(img_noisy, color_continuous_scale='gray')
fig.show()

import plotly.express as px

rng = np.random.default_rng()
noise_im = rng.standard_normal(size=img.shape)

fig = px.imshow(noise_im, color_continuous_scale='gray')
fig.show()


img_noisy = img + noise_im*np.sqrt(100) + 0
img_noisy[img_noisy > 255] = 255
img_noisy[img_noisy < 0] = 0

hist_n, bin_edges = np.histogram(img_noisy, bins = np.arange(257))

fig = make_subplots(rows=1, cols=2)
fig.add_trace(go.Image(z=np.stack((img_noisy, img_noisy, img_noisy), axis=2)), row=1, col=1)
fig.add_trace(go.Scatter(x=np.arange(256), y=hist_n, mode='lines',name='hist_noisy', line=dict(color='blue')), row=1, col=2)
fig.show()