  We test methods for measuring and characterizing rough profiles with emphasis
on measurements of the self-affine roughness exponent, and describes a simple
test to separate between roughness exponents originating from long range
correlations in the sign signs of the profile, and roughness exponents
originating from L{\'e}vy distributions of jumps. Based on tests on profiles
with known roughness exponents we find that the power spectrum density analysis
and the averaged wavelet coefficients method give the best estimates for
roughness exponents in the range 0.1 to 0.9. The error-bars are found to be
less than 0.03 for profile lengths larger than 256, and there are no systematic
bias in the estimates. We present quantitative estimates of the error-bars and
the systematic error and their dependence on the value of the roughness
exponent and the profile length. We also quantify how power-law noise can
modify the measured roughness exponent for measurement methods different from
the power spectrum density analysis and the second order correlation function
method.
