SunnerLi / DeepFuse.pytorch

The re-implementation of ICCV 2017 DeepFuse paper idea
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may be incorrect loss funtion? #2

Open JohnTargaryen opened 5 years ago

JohnTargaryen commented 5 years ago

hey there, I notice that your code for loss function in ssim_loss_function.py is quite similar to the code I found in https://stackoverflow.com/questions/39051451/ssim-ms-ssim-for-tensorflow

However, this seems to be SSIM LOSS function instead of MEF SSIM LOSS function. In K. Ma, K. Zeng, and Z. Wang. Perceptual quality assessment for multi-exposure image fusion. IEEE Transactions on Image Processing, 24(11):3345–3356, 2015. , the author mentioned that "Direct use of the SSIM algorithm [27], however, is impossible, which requires a single perfect quality reference image. "

The paper Deepfuse's work is exactly on MEF(multi-exposure image fusion), so I would think there should be differences between SSIM LOSS and MEF SSIM LOSS, in other words, the loss function in your code may be incorrect?

Look forward to your reply, thx

Henry-GongZY commented 2 years ago

hey there, I notice that your code for loss function in ssim_loss_function.py is quite similar to the code I found in https://stackoverflow.com/questions/39051451/ssim-ms-ssim-for-tensorflow

However, this seems to be SSIM LOSS function instead of MEF SSIM LOSS function. In K. Ma, K. Zeng, and Z. Wang. Perceptual quality assessment for multi-exposure image fusion. IEEE Transactions on Image Processing, 24(11):3345–3356, 2015. , the author mentioned that "Direct use of the SSIM algorithm [27], however, is impossible, which requires a single perfect quality reference image. "

The paper Deepfuse's work is exactly on MEF(multi-exposure image fusion), so I would think there should be differences between SSIM LOSS and MEF SSIM LOSS, in other words, the loss function in your code may be incorrect?

Look forward to your reply, thx

I totally agree with you, MEF-SSIM is quite different from SSIM indeed.