Reviewing Inpainting Techniques Using Diffusion Models: A Comprehensive Analysis and Evaluation

Inpainting is an image processing technique used to restore damaged or missing regions in images, traditionally applied in the restoration of deteriorated paintings and photographs. More recently, diffusion models have gained popularity for inpainting due to their efficient generation of high-quality results. This article provides a concise introduction to inpainting and diffusion models, covering essential concepts such as information loss, coherence, and realism. It also highlights prominent diffusion models used in inpainting and concludes with an assessment of their pros and cons. Ongoing research areas, including 3D image in painting and privacy protection, are identified, along with other emerging applications like multimedia content creation, image repair, biomedical implementations, and medical diagnostics. Inpainting, with its diverse potential applications, stands as a promising and versatile technique in the realm of image processing.