Noise2SR: Learning to Denoise from Super-Resolved Single Noisy Fluorescence Image

Fluorescence microscopy is a key driver to promote discoveries of biomedical research. However, with the limitation microscope hardware and characteristics observed samples, fluorescence images are susceptible noise. Recently, few self-supervised deep learning (DL) denoising methods have been proposed. training efficiency performance existing relatively low in real scene noise removal. To address this issue, paper proposed image method Noise2SR (N2SR) train simple effective model based on single noisy observation. Our designed for paired different dimensions. Benefiting from strategy, more efficiently able restore details Experimental results simulated removal show that outperforms two blind-spot methods. We envision has potential improve other kind scientific imaging quality.