compare_psnr 函数可能是你记错了或者从某个特定的教程、示例代码中看到的。在 scikit-image 库中,计算 PSNR(峰值信噪比)通常使用的是 peak_signal_noise_ratio 函数。这个函数位于 skimage.metrics 模块中。 你可以使用以下代码来导入并使用该函数: python from skimage.metrics import peak_signal_noise_ratio as ...
psnr_denoised =compare_psnr(img, denoised) psnr_denoised_1 =compare_psnr(img, denoised_1)# multi-level case should outperform single level caseassert_(psnr_denoised > psnr_denoised_1 > psnr_noisy)# invalid number of wavelet levels results in a ValueErrormax_level = pywt.dwt_max_level(...
# 需要导入模块: from skimage import measure [as 别名]# 或者: from skimage.measure importcompare_psnr[as 别名]def__compare_psnr(planes):a, b = planesif(a == b).all():# Avoid "Warning: divide by zero encountered in double_scalars" generated# by skimage.measure.compare_psnrwhen a and ...
modelname='ex_blkpsnr.slx'; open_system(modelname); The model computes the PSNR value for the noisy and the denoised image with respect to the original image and outputs as variables namedpsnr_noisyandpsnr_denoisedrespectively. The denoised image and the computed PSNR values are exported to ...
How to calculate PSNR of compressed images, and... Learn more about how to calculate psnr of a compressed image, psnr, image compression Image Processing Toolbox