By applying the basic principles of metrology we discuss how to define the standards that any experimental method to measure resolution has to obey. Our results clearly indicate the need to apply a calibration procedure when designing algorithms to estimate resolution to satisfy accuracy requirements. Similarly, the precision of an algorithm has to be clearly specified. We compare here the performances of a variety of commonly used implementations of published methods, with that of an algorithm based on an approach known to be reliable. Our results confirm that when an algorithm is designed with the clear intent of satisfying metrology requirements, it demonstrates excellent accuracy, precision, and lack of sensitivity to the noise level, as is desirable. As a consequence, the algorithm will have the ability to measure accurately the point spread function convoluted in the image, thus paving the way for quantitative deconvolution techniques.