Abstract

Subject of study. A scheme of screening better super-resolution reconstruction based on denoising conventional raw images with wide spectrum denoising is studied. Purpose of the work. The purpose is to improve the reconstruction effect of ultra-high-resolution images. To this end, reconstruction with noise reduction and compression of ordinary raw images and high-resolution images has been investigated. Method. A binned high-resolution raw image is a conventional raw image. Conventional raw images and high-resolution raw images are denoised with wide spectrum denoising, respectively. The conventional raw images and high-resolution raw images before and after denoising are reconstructed by compressed sensing. Main Results. The denoising ability of wide spectrum denoising based on high-resolution raw images is very stable and does not change with molecular density. The signal-to-noise ratio improves by approximately 8 dB. The denoising ability of wide spectrum denoising based on conventional raw images is not good. The signal-to-noise ratios of conventional raw images is 6 dB higher than that of high-resolution raw images. The signal-to-noise ratios of denoised high-resolution and conventional raw images are almost the same. Compressed sensing reconstruction of the denoised conventional raw images is inferior to that of denoised high-resolution raw images; however, it is better than that of high-resolution and conventional raw images. Practical significance. In conventional single-molecule localizations and super-resolution microscopy, the pixel size of a raw image is about equal to the standard deviation of the point spread function. Wide spectrum denoising can improve the conventional raw image denoising and reconstruction. However, better super-resolution microscopy can be achieved based on wide spectrum denoising and high-resolution raw images. Super-resolution microscopy of high-resolution raw images will become a new research point.

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