Submitted by ToTa_12 t3_yvtelj in MachineLearning
How much does it matter what settings (iso, f, exposure time) are used in datasets? Of course there are some specific cases, like imaging in dark conditions where the iso obviously needs to be large and the noise has to be handled. But in more general case, it seems like many datasets are acquired with auto settings. The quality assesment seems to be on the sharpness and relevancy. Is there any papers on the topic of how camera settings and lightning solutions affect the dataset quality or usability?
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.