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画像品質評価のPSNR, SSIMの実装と速度比較

Last updated at Posted at 2018-09-26

背景

from skimage.measure import compare_ssim, compare_psnr

をすると
compare_ssimcompare_psnrでSSIMとPSNRの評価ができる。
速度比較がしたい。

速度比較

from skimage.measure import compare_ssim, compare_psnr
import cv2
import time

def measurement(func, **kwargs):
    start = time.time()
    val = func(kwargs["img1"], kwargs["img2"])
    end = time.time()
    return val, end-start

img1 = cv2.imread("sample1.png", cv2.IMREAD_GRAYSCALE)
img2 = cv2.imread("sample2.png", cv2.IMREAD_GRAYSCALE)
print("ssim: %f, time: %lf[sec]" % measurement(compare_ssim, img1=img1, img2=img2))
print("psnr: %f, time: %lf[sec]" % measurement(compare_psnr, img1=img1, img2=img2))

# => ssim: 0.974289, time: 0.806180[sec]
# => psnr: 21.250949, time: 0.053643[sec]

結論

わかってはいたけどPSNRの方がめっちゃ早い。(15倍ぐらい)

おまけ

画像間の同じ座標のピクセルと値との差の合計pixel_diffとの比較をしてみる。

from skimage.measure import compare_ssim, compare_psnr
import cv2
import time
import numpy as np

def pixel_diff(img1, img2):
    return np.sum(np.absolute(img1 - img2))

def measurement(func, **kwargs):
    start = time.time()
    val = func(kwargs["img1"], kwargs["img2"])
    end = time.time()
    return val, end-start

img1 = cv2.imread("sample1.png", cv2.IMREAD_GRAYSCALE)
img2 = cv2.imread("sample2.png", cv2.IMREAD_GRAYSCALE)
print("ssim: %f, time: %lf[sec]" % measurement(compare_ssim, img1=img1, img2=img2))
print("psnr: %f, time: %lf[sec]" % measurement(compare_psnr, img1=img1, img2=img2))
print("pixel_diff: %f, time: %lf[sec]" % measurement(compare_psnr, img1=img1, img2=img2))

# => ssim: 0.996097, time: 0.734509[sec]
# => psnr: 29.721666, time: 0.046622[sec]
# => pixel_diff: 29.721666, time: 0.045121[sec]

参考

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