Imaging through a multimode optical fiber with principal component analysis and a variational autoencoder

Abstract

Abstract Imaging through the multi-mode fiber (MMF) becomes an attractive approach for gaining visual access to confined spaces. However, current imaging techniques through a MMF still encounter challenges including modal dispersion, complex wave-front shaping mechanism, and expensive light sources and modulations. This work proposed a cost-efficient setup with three light-emitting diodes as the illumination light source (including red, green, and blue light) and a hybrid model including the principal component analysis and a variational auto-encoder (PCAVAE) for reconstructing the transmitted images. The reconstructed images demonstrate high fidelity compared with their ground truth images. The average similarity index value of the reconstructed images is as high as 0.99. Experimental works indicated that the proposed approach was capable of rejecting 10% white noise in the imaging process. The proposed triple-color illumination method paves a cost-effective way of transmitting images through an MMF. The PCAVAE model established in this work demonstrates great potential for processing scrambled images transmitted by the MMF.