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deep-tempest
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Changed noise parameter from SNR to standard deviation

This commit is contained in:
Emilio Martínez 2023-02-26 20:44:18 -03:00
parent 8711529c5f
commit 059f280e99
1 changed files with 12 additions and 13 deletions
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25
scripts/folder_simulation.py
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@ -25,7 +25,7 @@ import sys
#%%
# Currently supporting png, jpg, jpeg, tif, tiff and gif extentions only
# Currently supporting png, jpg, jpeg, tif and gif extentions only
def get_images_names_from_folder (folder):
images_list = [image for image in os.listdir(folder) \
if image.endswith('.png') or image.endswith('.jpg') or image.endswith('.jpeg') or \
@ -46,7 +46,7 @@ def image_transmition_simulation(I, blanking=False):
return I_TMDS_Tx, I_TMDS.shape
def image_capture_simulation(I_Tx, h_total, v_total, N_harmonic, SNR,
def image_capture_simulation(I_Tx, h_total, v_total, N_harmonic, noise_std,
fps=60):
# Compute pixelrate and bitrate
@ -62,11 +62,10 @@ def image_capture_simulation(I_Tx, h_total, v_total, N_harmonic, SNR,
else:
I_Tx_continuous = I_Tx
# Add Gaussian noise according to SNR
if SNR > 0:
signal_power = np.sum(np.abs(np.fft.fft(I_Tx_continuous))**2/Nsamples)
noise_sigma = np.sqrt(signal_power/(10**(SNR/10)))
I_Tx_noisy = I_Tx_continuous + np.random.normal(0, noise_sigma, Nsamples)
# Add Gaussian noise
if noise_std > 0:
noise_sigma = noise_std/15.968719423 # sqrt(255)~15.968719423
I_Tx_noisy = I_Tx_continuous + np.random.normal(0, noise_sigma, Nsamples) + 1j*np.random.normal(0, noise_sigma,N_samples)
else:
I_Tx_noisy = I_Tx_continuous
@ -148,8 +147,8 @@ def main():
I_Tx, resolution = image_transmition_simulation(I)
v_res, h_res, _ = resolution
# Possible SNR simulation values
SNRs = np.array([ 0, 60, 65, 70, 75, 80, 85, 90, 95, 100])
# Possible std dev noise simulation values
noise_stds = np.array([ 0, 5, 10, 15, 20, 25, 40, 50])
# Make five simulations for each image
@ -159,11 +158,11 @@ def main():
N_harmonic = np.random.randint(1,10)
# Choose random SNR value (SNR=0 for no noise)
SNR = np.random.choice(SNRs)
noise_std = np.random.choice(noise_stds)
I_capture = image_capture_simulation(I_Tx, h_res, v_res, N_harmonic, SNR)
I_capture = image_capture_simulation(I_Tx, h_res, v_res, N_harmonic, noise_std)
path = subfolder_path+'/'+imagename+'_'+str(N_harmonic)+'harm_'+str(SNR)+"dB.png"
path = subfolder_path+'/'+imagename+'_'+str(N_harmonic)+'harm_'+str(noise_std)+"std.png"
save_simulation_image(I_capture,path)
@ -176,7 +175,7 @@ def main():
t_image = t2_image-t1_image
print('Tiempo de simulación para '+image+':','{:.2f}'.format(t_image)+'s')
print('Tiempo de la primer simulación de '+image+':','{:.2f}'.format(t_image)+'s\n')
if __name__ == "__main__":
main()