Conceptually, the developed algorithm utilizes the physical meaning behind the spectral-frequency profile , which allows to obtain several independent parameters of sample’s organization by evaluating at different . First, no scattering events occur at , which we use to measure . Second, at , is predominantly defined by the amount of light reflected at the sample–substrate interface, which we use to measure . Third, at , represents the amount of scattering from within the sample, which determines . Essentially, the reflection at is defined by the two-dimensional (2-D) statistics of RI distribution, , and the scattering at is defined by the 3-D statistics of RI, which is why and probe the sample structure in a truly independent manner. We also note that due to the statistical homogeneity considered here, could be computed from the value of for virtually any between 0 and . However, we have chosen to calculate at the midpoint of in order to minimize the inevitable (due the finite spectral bandwidth) contributions from surface roughness at low and at . Finally, at low , also contains information about the sample surface roughness profile in addition to its internal inhomogeneity.16 Since the present work does not aim to measure surface statistics, the surface-related contributions are simply removed from the signal.