  We developed a minimum gradient based method to track ridge features in 2D
image plot, which is a typical data representation in many momentum resolved
spectroscopy experiments. Through both analytic formulation and numerical
simulation, we compare this new method with existing DC (distribution curve)
based and higher order derivative based analyses. We find that the new method
has good noise resilience and enhanced contrast especially for weak intensity
features, meanwhile preserves the quantitative local maxima information from
the raw image. An algorithm is proposed to extract 1D ridge dispersion from the
2D image plot, whose quantitative application to angle-resolved photoemission
spectroscopy measurements on high temperature superconductors is demonstrated.
