The ratio of x-y unit and z unit influences the proportional coefficient of σ _Noise -μ _G and σ _Noise - σ _G relationship. Using a strategy similar to what is presented in Fig. S5, we simulated 3D normal ground noise images (800*800*25) with a variable standard deviation (STD) and mean fixed to 90. Next, the z-axis was interpolated by the fold of a scaling factor, defined as z-unit/xy-unit, the second variable. Like the 2D data structure, at a given scaling factor, the mean and STD of noise gradient is proportional only to the STD of native noise. Then, we adopt a mathematical model μ_Gorσ_G = k_s(Scalingfactor)σ_Noise to accurately describe the numeric relationship between the gradient and native value of background noise. By a piecewise polynomial regression, we obtain a prediction model that accurately (R² = 1) calculate k_s and therefore determine the relationship between mean/STD of the noise gradient and the native noise values. (a and b) the relationship between mean of noise gradient and STD of noise. (c and d) the relationship between mean of noise gradient and STD of noise.