Submitted by ToTa_12 t3_yvtelj in MachineLearning
tdgros t1_iwg1xic wrote
When talking about image restoration: denoising, deblurring, super-resolution... those settings matter a lot, obviously: ISO determines the noise, exposure time participates in the blur and the f-number affects the sharpness of the image. So they are very useful inputs, including in good lighting conditions by the way.
ToTa_12 OP t1_iwg4yfa wrote
Yes they are important inputs, but when considering the collection of dataset it seems like people don't really pay attention to the settings, if it's not directly related to the application.
tdgros t1_iwg6php wrote
Yes. When collecting a "natural" dataset, the variety of camera settings just reflects how images are taken in the wild: sometimes in day time, sometimes in night time. In some cases, you would even want a variety of cameras as well as they handle different conditions differently. If your task is camera-agnostic, then you want to marginalize the camera settings.
ToTa_12 OP t1_iwg93fj wrote
True, thanks for the answers. It's an interesting note to think about how different cameras determine the auto settings.
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