MobileViT-GAN: A Generative Model for Low Bitrate Image Coding

Effective image coding techniques are crucial for digital image storage and transmission. Traditional methods struggle to maintain high visual quality at low bitrates. In this paper, we present MobileViT-GAN, a novel generative adversarial network (GAN) architecture for low bitrate image compression. We propose a lightweight transformer-based discriminator to improve coding performance, compared to convolutional neural network-based discriminators. Additionally, we introduce a smoothness loss function to mitigate artifacts in decoded images, further improving visual quality in low bitrate image coding. We evaluate our proposed method against traditional and state-of-the-art GAN-based image compression techniques, showcasing its superiority in terms of compression ratio and decoded image quality.