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tutorial48_reference_based_image_quality.py
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#Video Playlist: https://www.youtube.com/playlist?list=PLHae9ggVvqPgyRQQOtENr6hK0m1UquGaG
"""
Older versions of scikit-image: older than 0.16
https://scikit-image.org/docs/dev/api/skimage.measure.html
Newer scikit-image: 0.17 or later
https://scikit-image.org/docs/stable/api/skimage.metrics.html
https://pypi.org/project/sewar/
https://sewar.readthedocs.io/en/latest/_modules/sewar/full_ref.html#ergas
"""
import cv2
import numpy as np
from sewar import full_ref
from skimage import measure, metrics
#Reference and image to be compared must be of the same size
ref_img = cv2.imread("images/noisy_images/sandstone.tif", 1)
img = cv2.imread("images/noisy_images/sandstone_25sigma_noisy.tif", 1)
################################################################
#skimage tools
#Mean square error
#Older skimage versions, older than 0.17: skimage.measure.compare_mse
#skimage.metrics.mean_squared_error
mse_skimg = metrics.mean_squared_error(ref_img, img)
print("MSE: based on scikit-image = ", mse_skimg)
#Same as PSNR available in sewar
#Older versions of skimage: skimage.measure.compare_psnr
#skimage.metrics.peak_signal_noise_ratio
psnr_skimg = metrics.peak_signal_noise_ratio(ref_img, img, data_range=None)
print("PSNR: based on scikit-image = ", psnr_skimg)
#Normalized root mean squared error
#Older versions of skimage: skimage.measure.compare_nrmse
rmse_skimg = metrics.normalized_root_mse(ref_img, img)
print("RMSE: based on scikit-image = ", rmse_skimg)
from skimage.metrics import structural_similarity as ssim
ssim_skimg = ssim(ref_img, img,
data_range = img.max() - img.min(),
multichannel = True)
print("SSIM: based on scikit-image = ", ssim_skimg)
###############################################################
#ERGAS Global relative error
"""calculates global relative error
GT: first (original) input image.
P: second (deformed) input image.
r: ratio of high resolution to low resolution (default=4).
ws: sliding window size (default = 8).
:returns: float -- ergas value.
"""
ergas_img = full_ref.ergas(ref_img, img, r=4, ws=8)
print("EGRAS: global relative error = ", ergas_img)
####################################################################
#Multiscale structural similarity index
"""calculates multi-scale structural similarity index (ms-ssim).
:param GT: first (original) input image.
:param P: second (deformed) input image.
:param weights: weights for each scale (default = [0.0448, 0.2856, 0.3001, 0.2363, 0.1333]).
:param ws: sliding window size (default = 11).
:param K1: First constant for SSIM (default = 0.01).
:param K2: Second constant for SSIM (default = 0.03).
:param MAX: Maximum value of datarange (if None, MAX is calculated using image dtype).
:returns: float -- ms-ssim value.
"""
msssim_img=full_ref.msssim(ref_img, img, weights=[0.0448, 0.2856, 0.3001, 0.2363, 0.1333], ws=11, K1=0.01, K2=0.03, MAX=None)
print("MSSSIM: multi-scale structural similarity index = ", msssim_img)
##############################################################################
#PSNR
"""calculates peak signal-to-noise ratio (psnr).
:param GT: first (original) input image.
:param P: second (deformed) input image.
:param MAX: maximum value of datarange (if None, MAX is calculated using image dtype).
:returns: float -- psnr value in dB.
"""
psnr_img=full_ref.psnr(ref_img, img, MAX=None)
print("PSNR: peak signal-to-noise ratio = ", psnr_img)
##########################################################################
#PSNRB: Calculates PSNR with Blocking Effect Factor for a given pair of images (PSNR-B)
"""Calculates PSNR with Blocking Effect Factor for a given pair of images (PSNR-B)
:param GT: first (original) input image in YCbCr format or Grayscale.
:param P: second (corrected) input image in YCbCr format or Grayscale..
:return: float -- psnr_b.
"""
#psnrb_img = full_ref.psnrb(ref_img, img)
#print("PSNRB: peak signal-to-noise ratio with blocking effect = ", psnrb_img)
#######################################################################
#relative average spectral error (rase)
"""calculates relative average spectral error (rase).
:param GT: first (original) input image.
:param P: second (deformed) input image.
:param ws: sliding window size (default = 8).
:returns: float -- rase value.
"""
RASE_img = full_ref.rase(ref_img, img, ws=8)
#print("RASE: relative average spectral error = ", RASE_img)
######################################################################
#RMSE
"""calculates root mean squared error (rmse).
:param GT: first (original) input image.
:param P: second (deformed) input image.
:returns: float -- rmse value.
"""
rmse_img = full_ref.rmse(ref_img, img)
print("RMSE: root mean squared error = ", rmse_img)
######################################################################
#root mean squared error (rmse) using sliding window
"""calculates root mean squared error (rmse) using sliding window.
:param GT: first (original) input image.
:param P: second (deformed) input image.
:param ws: sliding window size (default = 8).
:returns: tuple -- rmse value,rmse map.
"""
rmse_sw_img = full_ref.rmse_sw(ref_img, img, ws=8)
#print("RMSE_SW: root mean squared error with sliding window = ", rmse_sw_img)
#########################################################################
#calculates spectral angle mapper (sam).
"""calculates spectral angle mapper (sam).
:param GT: first (original) input image.
:param P: second (deformed) input image.
:returns: float -- sam value.
"""
ref_sam_img = full_ref.sam(ref_img, img)
print("REF_SAM: spectral angle mapper = ", ref_sam_img)
######################################################################
#Spatial correlation coefficient
#full_ref.scc(ref_img, img, win=[[-1, -1, -1], [-1, 8, -1], [-1, -1, -1]], ws=8)
#Structural similarity index
"""calculates structural similarity index (ssim).
:param GT: first (original) input image.
:param P: second (deformed) input image.
:param ws: sliding window size (default = 8).
:param K1: First constant for SSIM (default = 0.01).
:param K2: Second constant for SSIM (default = 0.03).
:param MAX: Maximum value of datarange (if None, MAX is calculated using image dtype).
:returns: tuple -- ssim value, cs value.
"""
ssim_img = full_ref.ssim(ref_img, img, ws=11, K1=0.01, K2=0.03, MAX=None, fltr_specs=None, mode='valid')
print("SSIM: structural similarity index = ", ssim_img)
##############################################################################
#Universal image quality index
"""calculates universal image quality index (uqi).
:param GT: first (original) input image.
:param P: second (deformed) input image.
:param ws: sliding window size (default = 8).
:returns: float -- uqi value.
"""
UQI_img = full_ref.uqi(ref_img, img, ws=8)
print("UQI: universal image quality index = ", UQI_img)
##############################################################################
#Pixel Based Visual Information Fidelity (vif-p)
"""calculates Pixel Based Visual Information Fidelity (vif-p).
:param GT: first (original) input image.
:param P: second (deformed) input image.
:param sigma_nsq: variance of the visual noise (default = 2)
:returns: float -- vif-p value.
"""
VIFP_img = full_ref.vifp(ref_img, img, sigma_nsq=2)
print("VIFP: Pixel Based Visual Information Fidelity = ", VIFP_img)