Inquiry about the signal-independent noise map calculated in the code and the setup of single image training

[whtang906]

Hi, it's me again! I am really interested in your work! But I have found some questions about the technical detail.

According to figure 3a of the paper, you feed the signal-independent noise map with signal-dependent noise map into the network again and expect to get . I have some questions about this part.

1. Why we need to feed the signal-dependent noise map as well? Why not just feed the signal-independent noise map and expect to get .
2. According to the provided source code, it seems the signal-dependent noise map wasn't fed into the network? https://github.com/Reyhanehne/CVF-SID_PyTorch/blob/c89242a4ef5cc98481404192392a6f76e0fb0ec9/src/trainer/trainer.py#L87

Apart from this, can you share more detail about the setup of single image training? For example, the hyperparameters you have used (epochs, learning rate, etc) for the image shown in the appendix.

Thank you so much!