Fig. 2: Modified approach to remove chequerboard artefacts found when denoising.

a Example input dual-channel image (cropped). b Denoising result showing clear chequerboard artefacts where denoising was performed with an early version of our underlying modified Noise2Void UNet using standard pixel-masking (during training) and transposed convolutions for upsampling. c The final Noise2Void UNet architecture, used elsewhere in this work, with chequerboard artefacts significantly diminished. The architectures of c and b have different upsampling and jittered pixel-masking. An overview of the modified Noise2Void training algorithm can be seen in (d), with the masked pixels jittered/randomly translated by a small amount. Note that, while only annular dark field images are shown in (d), training is performed on the full dual-channel images.