Application of Artificial Intelligence to Image Processing: Advantages and Prognosis

Dear Colleagues,

The tremendous progress that has recently been made in artificial intelligence (AI) has stimulated numerous novel concepts and technologies in image processing, including multimodal data fusion, real-time image analysis, and high-dimensional image processing. The rapid development of AI has significantly enhanced the accuracy, speed, and automation of image processing tasks, such as object detection, segmentation, and classification, with broad applications in healthcare, autonomous driving, and edge computing. Among these technologies, one of the most exciting directions is the integration of generative AI in image processing, which introduces new possibilities for image generation, knowledge transfer, and image reconstruction. Another promising direction is physics-informed machine learning, which facilitates image processing with specific requirements in practical applications. Moreover, the emerging fields of self-supervised learning and federated learning provide efficient tools for image understanding and privacy protection, respectively.

This Special Issue aims to establish a platform for researchers to share their latest research outcomes and innovations in the emerging field of artificial intelligence for image processing. We welcome contributions to both theoretical fundamentals and practical applications related to AI-driven image processing. Particularly, we encourage submissions that explore the use of generative and self-supervised learning to address image synthesis and interpretation. We also encourage submissions focusing on physics-informed machine learning in image processing, integrating physical principles and data statistics. In addition, we strongly welcome submissions about the application of AI-assisted image processing to science and engineering problems with the consideration of efficiency and security, such as semantic communications, private distributed edge computing, future additive manufacturing, biomedical imaging, remote sensing, multimodal sensor fusion, and autonomous driving.

The scope of this Special Issue shall cover a wide range of topics in AI and image processing, including but not limited to the following:

• Generative learning for image synthesis;
• Self-supervised image processing;
• Physics-informed machine learning for practical image processing;
• Multimodal data fusion;
• Federated learning for imaging data privacy;
• Applications of AI-assisted image processing in scientific and engineering problems.

We invite original and high-quality submissions related to the theme of this Special Issue. We believe this Special Issue will provide good opportunities for researchers to share their latest outcomes and insightful views on the advantages and prognosis of the application of AI to image processing, which shall also inspire future AI technologies for image processing, together with its practical applications.

Dr. Songyang Zhang
Dr. Shuai Zhang
Guest Editors

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• image processing
• generative learning
• self-supervised learning
• physics-informed machine learning
• distributed learning