Using photon statistics to boost microscopy resolution

The magnifying power of light microscopy exerts a universal fascination that lasts a lifetime. Soon enough, however, users of optical microscopes learn (or should learn) that this power comes with limitations due to diffraction, as explained by Ernst Abbe (1) more than a century ago: any object, no matter how small, will be imaged by a conventional optical system as a finite-sized spot, with a minimum dimension obtained for point-like objects (such as single molecules) approximately equal to the wavelength of light, λ, multiplied by the optical magnification, M, and divided by the numerical aperture (N.A.) (Fig. 1 A). The radius of this so-called point-spread function (PSF) can be used as a convenient criterion to define an upper limit to the minimum distance below which two nearby objects in the object plane cannot be distinguished (Fig. 1 B). It has been known for some time that this Rayleigh criterion (2) is a bit too conservative, and that objects significantly closer can still be resolved with careful image analysis or clever illumination and detection schemes. In an article published in a recent issue of PNAS, Ram et al. (3) revisited this question and demonstrated that there is really no limit to how close two identical point-like objects can be and still have distances measurable with almost arbitrary precision by using conventional microscopy.