Reference-State Decoupling Regeneration for Restoring Image Editability

Protective perturbations can severely disrupt downstream image editing while remaining visually similar to clean images. Existing diffusion-based purification methods typically initialize generation from a noised protected image, causing image content and protective perturbations to enter the initial generative state together. Stronger noising may suppress the perturbations but also discard the content required for faithful editing. To better understand this trade-off, we distinguish two roles of the protected image: state initialization, which directly introduces protected pixels into the generative state, and reference conditioning, which provides image information to guide generation. We investigate how these distinct input roles affect editability restoration under protective perturbations. A diagnostic experiment shows that progressively reducing the protected image's contribution to the initial state improves editability restoration while maintaining comparable reconstruction fidelity, with independent initialization achieving the highest Recovery. Motivated by this finding, we propose Reference-State Decoupled Regeneration (RSDR), which retains the protected image as a fixed reference while initializing the evolving pixel state from independent Gaussian noise. Time-dependent reference features guide the state trajectory through a lightweight interface, enabling content-preserving regeneration without directly injecting protected pixels into the initial state. Experiments across four protection methods demonstrate consistent improvements in editability restoration over existing baselines. These results demonstrate the effectiveness of decoupling reference conditioning from state initialization for restoring image editability under protective perturbations. Code will be released upon acceptance.