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Hi, I came across this while looking for a PyTorch implementation of SSIM. On the Tensorflow page for SSIM it's mentioned that "Note: The true SSIM is only defined on grayscale. This function does not perform any colorspace transform. (If the input is already YUV, then it will compute YUV SSIM average.)"
I was wondering if there are any conversions (either to YUV or to grayscale) that I would have to do to use this. My images are all RGB images.
The text was updated successfully, but these errors were encountered:
Hi @VainF, thank you for the response! Please correct me if I'm mistaken but my understanding of SSIM is that we should calculate it based on luminance. In the case of a YUV image we consider only the Y (luminance) channel and in the case of a grayscale image, we only have luminance to work with. If you are calculating SSIM separately for each channel and then taking the mean, then I think the results are slightly off since converting RGB to luminance follows a different formula (Ref: https://en.wikipedia.org/wiki/Relative_luminance)
Hi, I came across this while looking for a PyTorch implementation of SSIM. On the Tensorflow page for SSIM it's mentioned that "Note: The true SSIM is only defined on grayscale. This function does not perform any colorspace transform. (If the input is already YUV, then it will compute YUV SSIM average.)"
I was wondering if there are any conversions (either to YUV or to grayscale) that I would have to do to use this. My images are all RGB images.
The text was updated successfully, but these errors were encountered: