In this comprehensive review, we delve into super-resolution optical imaging techniques and their diverse applications. Our primary focus is on linear optics super-resolution methods, encompassing a wide array of concepts ranging from time multiplexing, ptychography, and deep learning-based microscopy to compressive sensing and random phase encoding techniques. Additionally, we explore compressed sensing, non-spatial resolution improvement, and sparsity-based geometric super-resolution. Furthermore, we investigate various methods based on field of view, wavelength, coherence, polarization, gray level, and code division multiplexing, as well as localization microscopy. Our review extends to stimulated emission depletion microscopy via pump- probe super-resolution techniques, providing a detailed analysis of their working applications. We then shift our attention to near-field scanning optical microscopy, discussing its principles and applications in various fields. Recent techniques such as Microsphere-assisted microscopy, Airyscan, mean-shift super-resolution, photothermal relaxation localization microscopy, and a novel structured illumination-based super-resolution technique enables tomography of semi-transparent samples by investigating their refractive index thus providing a 3D map of the samples. Moreover, we examine the concept of super-resolution in a nonlinear medium, highlighting its unique characteristics and potential benefits. Finally, we discuss the future perspectives and trends of super-resolution optical imaging, offering insights into its potential evolution and impact on the field.
