MSARNet: Efficient JPEG Artifact Removal Using Multi-Stage Style Network

With the rapid development of photography and information processing technologies, we use more and more digital images in our daily lives. JPEG is one of the most widely used digital image formats because of its high efficiency and widespread support. JPEG Artifact Removal is a task that removes artifacts in JPEG images, such as noise and color distortion in JPEG images. Existing methods for JPEG Artifact Removal require high computational costs, which means stricter performance requirements or longer processing time. We propose a novel method for JPEG Artifact Removal named Multi-Stage style Artifacts Removal Net (MSARNet), which meets high performance, high versatility, and low computational cost. MSARNet adopts multi-stage processing, and images are processed in processing stages step by step. This process enables our proposed method to deal with different types of images effectively and efficiently. Additionally, MSARNet estimates the quality value of the input image, which contributes to effective feature processing. Experimental results show that our proposed method handles various artifacts well and outperforms existing methods in artifact removal tasks with lower computational costs.