Consider the stochastic differential equation of diffusion type driven by Brownian motion dX(t, ω) = μX(t, ω)dt + σX(t, ω)dB (t, ω) where B(t, ω) = limn→∞ B n (t, ω) is a Brownian motion, n is a positive integer, t is time variable, ω is state variable, μ and σ are constants. The solution X(t, ω) is represented by images. Solution contains a term of Brownian motion. Therefore, the image of a solution needs the image of Brownian motion. We have obtained the images of Brownian motion and solution X(t, ω) for different combinations of parameters (μ, σ, n and p. Note that p controls the degree of randomness in Brownian motion. Degree of randomness in Brownian motion is maximum for p = 0.5). The key observations from image analysis are 1. less randomness is visualized for p values away from 0.5, 2. colors in images for n = 10, 000 is more than the color in images for n = 10, 000, 00, and 3. randomness in solution depends on μ and σ also. More randomness is visualized as μ − 1 2 σ 2 is away from 0. The observations are consistent with mathematical analysis of the solution X(t, ω).