Nowadays, the use of super-resolution microscopy (SRM) is increasing globally due to its potential application in several fields of life sciences. However, a detailed and comprehensive guide is necessary for understanding a single-frame image's resolution limit. This study was performed to provide information about the structural organisation of isolated cellulose fibres from garlic and agave wastes through fluorophore-based techniques and image analysis algorithms. Confocal microscopy provided overall information on the cellulose fibres' microstructure, while techniques such as total internal reflection fluorescence microscopy facilitated the study of the plant fibres' surface structures at a sub-micrometric scale. Furthermore, SIM and single-molecule localisation microscopy (SMLM) using the PALM reconstruction wizard can resolve the network of cellulose fibres at the nanometric level. In contrast, the mean shift super-resolution (MSSR) algorithm successfully determined nanometric structures from confocal microscopy images. Atomic force microscopy was used as a microscopy technique for measuring the size of the fibres. Similar fibre sizes to those evaluated with SIM and SMLM were found using the MSSR algorithm and AFM. However, the MSSR algorithm must be cautiously applied because the selection of thresholding parameters still depends on human visual perception. Therefore, this contribution provides a comparative study of SRM techniques and MSSR algorithm using cellulose fibres as reference material to evaluate the performance of a mathematical algorithm for image processing of bioimages at a nanometric scale. In addition, this work could act as a simple guide for improving the lateral resolution of single-frame fluorescence bioimages when SRM facilities are unavailable.