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TST: compare PSNR in the wavelet denoising tests

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Gregory R. Lee
2016-08-12 08:23:20 -04:00
parent 72577e9764
commit 87936c0b09
1 changed files with 20 additions and 9 deletions
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skimage/restoration/tests/test_denoise.py
+20 -9
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@@ -3,7 +3,7 @@ from numpy.testing import run_module_suite, assert_raises, assert_equal
from skimage import restoration, data, color, img_as_float, measure
from skimage._shared._warnings import expected_warnings
from skimage.measure import compare_ssim
from skimage.measure import compare_psnr
np.random.seed(1234)
@@ -311,17 +311,28 @@ def test_no_denoising_for_small_h():
def test_wavelet_denoising():
for img, multichannel in [(astro_gray, False), (astro, True)]:
noisy = img.copy() + 0.1 * np.random.randn(*(img.shape))
sigma = 0.1
noisy = img.copy() + sigma * np.random.randn(*(img.shape))
noisy = np.clip(noisy, 0, 1)
# less energy in signal
denoised = restoration.denoise_wavelet(noisy, sigma=0.3,
multichannel=multichannel)
assert denoised.sum()**2 <= img.sum()**2
# test changing noise_std (higher threshold, so less energy in signal)
res1 = restoration.denoise_wavelet(noisy, sigma=0.2,
# Verify that SNR is improved when true sigma is used
denoised = restoration.denoise_wavelet(noisy, sigma=sigma,
multichannel=multichannel)
psnr_noisy = compare_psnr(img, noisy)
psnr_denoised = compare_psnr(img, denoised)
assert psnr_denoised > psnr_noisy
# Verify that SNR is improved with internally estimated sigma
denoised = restoration.denoise_wavelet(noisy,
multichannel=multichannel)
psnr_noisy = compare_psnr(img, noisy)
psnr_denoised = compare_psnr(img, denoised)
assert psnr_denoised > psnr_noisy
# Test changing noise_std (higher threshold, so less energy in signal)
res1 = restoration.denoise_wavelet(noisy, sigma=2*sigma,
multichannel=multichannel)
res2 = restoration.denoise_wavelet(noisy, sigma=0.1,
res2 = restoration.denoise_wavelet(noisy, sigma=sigma,
multichannel=multichannel)
assert (res1.sum()**2 <= res2.sum()**2)