Raw-JPEG Adapter: Efficient Raw Image Compression with JPEG

Digital cameras digitize scene light into linear raw representations,which the image signal processor (ISP) converts into display-ready outputs. Whileraw data preserves full sensor information—valuable for editing and vision tasks—formats such as Digital Negative (DNG) require large storage, making them im-practical in constrained scenarios. In contrast, JPEG is a widely supported format,offering high compression efficiency and broad compatibility, but it is not well-suited for raw storage. This paper presents Raw-JPEG Adapter, a lightweight,learnable, and invertible pre-processing pipeline that adapts raw images for stan-dard JPEG compression. Our method applies spatial and optional frequency-domain transforms, with compact parameters stored in the JPEG comment field,enabling accurate raw reconstruction. Experiments across multiple datasets showthat our method achieves higher fidelity than direct JPEG storage, supports othercodecs, and provides a favorable trade-off between compression ratio and recon-struction accuracy.