A Novel Visible-Infrared Image Compression Framework for High-Value Target Protection

The joint compression of visible-infrared images is crucial for military and surveillance applications. The challenge lies in the protection of high-value targets (HVT) while maintaining high compression efficiency. This paper proposes a novel dual-stream compression framework that effectively addresses this challenge. In our framework, the sensitive HVT infrared signatures are concealed within the visible image stream, while residual infrared image is encoded separately. This dual-stream compression framework introduces three key innovations. 1) HVT protection: The HVT information is physically isolated and hidden within public visible images through a dedicated concealment stream; 2) Key-conditioned reconstruction: A novel decoding mechanism enables active camouflage by replacing HVTs with plausible background content when unauthorized access is detected; 3) Unified optimization: The framework integrates compression efficiency and HVT protection within an endto- end trainable network. Extensive experiments demonstrate that our approach achieves state-of-the-art compression performance while providing superior HVT protection, significantly outperforming traditional encrypt-then-compress methods. The code and weights are open-source athttps://github.com/eecoder-dyf/rgbir-compress.