Embodiments are directed to accurately measuring a distance between a “true probability distribution: q” and a “probability distribution determined from a model of a generator: p” by D(x,y) of cGANs, so that a generated image may be made closer to a true image. A method of generating an image by using a conditional generative adversarial network constituted by two neural networks which are a generator and a discriminator, in which the discriminator outputs a result obtained from an arithmetic operation using a model of the following equation: f(x,y;θ):=f1(x,y;θ)+f2(x;θ)=yTVϕθΦ(x)+ψθΨ(ϕθΦ(x)).