  One of the most effective orthogonal moments, discrete Racah polynomials
(DRPs) and their moments are used in many disciplines of sciences, including
image processing, and computer vision. Moments are the projections of a signal
on the polynomial basis functions. Racah polynomials were introduced by Wilson
and modified by Zhu for image processing and they are orthogonal on a discrete
set of samples. However, when the moment order is high, they experience the
issue of numerical instability. In this paper, we propose a new algorithm for
the computation of DRPs coefficients called Improved Stabilization (ImSt). In
the proposed algorithm, {the DRP plane is partitioned into four parts, which
are asymmetric because they rely on the values of the polynomial size and the
DRP parameters.} The logarithmic gamma function is utilized to compute the
initial values, which empower the computation of the initial value for a wide
range of DRP parameter values as well as large size of the polynomials. In
addition, a new formula is used to compute the values of the initial sets based
on the initial value. Moreover, we optimized the use of the stabilizing
condition in specific parts of the algorithm. ImSt works for wider range of
parameters until higher degree than the current algorithms. We compare it with
the other methods in a number of experiments.
