We introduce an innovative approach for reducing speckle noise in holographic reconstruction images utilizing the Transformer architecture. This approach not only effectively captures speckle noise from digital holographic images but also better preserves details in images, owing to the characteristics of the Swin Transformer in globally and locally capturing relationships between image features. The network is trained using a large dataset with a distribution similar to real speckle noise. Experimental results demonstrate outstanding denoising performance of the proposed method and effectively preserving the details.
A large-scale and low-cost plasmonic nanodisk/hole array on flexible substrate for advanced biochemical sensing detection application is demonstrated by using the combined fabrication method of vacuum coating and nanoimprinting. Two distinct resonance dips from the proposed quasi-3D nanodisk/hole array are observed and analyzed at the nonzero incidence angle, exhibiting excellent sensing performance with both the bulk and surface sensitivity. Furthermore, the highly localized electromagnetic field within the nanodisk/hole array enables it to detect bovine serum albumin biomolecule at an ultra-low concentration of 100 nM, and Hg2+ specific detection with the detection limit as small as 0.26 μM. This large-scale and cheap sensing chip possesses broad applications prospects in the development of medical point-of-care diagnostics and drug discovery research.