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Image frames obtained in darkness are special. Just multiplying by a constantdoesn't restore the image. Shot noise, quantization effects and cameranon-linearities mean that colors and relative light levels are estimatedpoorly. Current methods learn a mapping using real dark-bright image pairs.These are very hard to capture. A recent paper has shown that simulated datapairs produce real improvements in restoration, likely because huge volumes ofsimulated data are easy to obtain. In this paper, we show that respectingequivariance -- the color of a restored pixel should be the same, however theimage is cropped -- produces real improvements over the state of the art forrestoration. We show that a scale selection mechanism can be used to improvereconstructions. Finally, we show that our approach produces improvements onvideo restoration as well. Our methods are evaluated both quantitatively andqualitatively.

Long Scale Error Control in Low Light Image and Video Enhancement Using Equivariance