Benjamin_Loison/Robust_image_source_identification_on_modern_smartphones
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Add Gaussian filter to blur images when using mean as denoiser

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https://docs.scipy.org/doc/scipy-1.13.0/reference/generated/scipy.ndimage.gaussian_filter.html#ba1e4df0-d4be-47c2-81e5-059286837a2b.
This commit is contained in:
Benjamin Loison 2024-04-26 04:39:06 +02:00
parent 9641641b61
commit 3ffcd33efe
Signed by: Benjamin_Loison
SSH Key Fingerprint: SHA256:BtnEgYTlHdOg1u+RmYcDE0mnfz1rhv5dSbQ2gyxW8B8
1 changed files with 5 additions and 3 deletions
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8
datasets/raise/extract_noise.py
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@ -10,6 +10,7 @@ import csv
import rawpy
from utils import Color
import matplotlib.pyplot as plt
from scipy.ndimage import gaussian_filter
imagesFolderPath = 'rafael/arw'
imagesFolderPathFileName = imagesFolderPath.replace('/', '_')
@ -100,7 +101,7 @@ def getImageNpArray(imageFileName, computeExtremes, color):
maxColor = colorRawImageVisibleMax
return
if imageFileName.endswith('.NEF') or imageFileName.endswith('.ARW'):
if (imageFileName.endswith('.NEF') or imageFileName.endswith('.ARW')) and denoiser != 'mean':
imageNpArray = (imageNpArray - minColor) / (maxColor - minColor)
# Pay attention to range of values expected by the denoiser.
# Indeed if provide the thousands valued raw image, then the denoiser only returns values between 0 and 1 and making the difference between both look pointless.
@ -128,7 +129,7 @@ def treatImage(imageFileName, computeExtremes = False, color = None):
mean = ((mean * numberOfImagesInMean) + imageNoiseNpArray) / (numberOfImagesInMean + 1)
numberOfImagesInMean += 1
if minColor is None or maxColor is None:
if (minColor is None or maxColor is None) and denoiser != 'mean':
# Assuming same intensity scale across color channels.
for imageFileName in tqdm(imagesFileNames, 'Computing extremes of images'):
for color in colors:
@ -148,8 +149,9 @@ if denoiser == 'mean':
for color in colors:
colorMean = None
numberOfImagesInColorMean = 0
for imageFileName in tqdm(imagesFileNames, f'Computing mean of {color colored images'):
for imageFileName in tqdm(imagesFileNames, f'Computing mean of {color} colored images'):
imageNpArray = getImageNpArray(imageFileName, False, color)
imageNpArray = gaussian_filter(imageNpArray, sigma = 5)
if colorMean is None:
colorMean = imageNpArray
else: