Abstract: An electronic device and method for image component generation based on application of iterative learning on autoencoder model and transformer model is provided. The electronic device fine-tunes, based on first training data including a first set of images, an autoencoder model and a transformer model. The autoencoder model includes an encoder model, a learned codebook, a generator model, and a discriminator model. The electronic device selects a subset of images from the first training data. The electronic device applies the encoder model on the selected subset of images. The electronic device generates second training data including a second set of images, based on the application of the encoder model. The generated second training data corresponds to a quantized latent representation of the selected subset of images. The electronic device pre-trains the autoencoder model to create a next generation of the autoencoder model, based on the generated second training data.