NRGMark: Localized Watermarking for Energy Transparency in Images

We present NRGMark, a region-based image watermarking framework to embed energy use and provenance metadata into images. Targeting composite graphic designs such as posters, NRGMark enables imperceptible watermarking of distinct visual elements each carrying independent metadata on their environmental impact, such as the energy consumption associated with generative AI (GenAI) use. NRGMark extends image watermark encoder-decoder models by incorporating an object localization network to detect and decode multiple watermarked regions within a document, even under image transformations and physical print-scan degradation. NRGMark interoperates with several watermarking techniques and the emerging C2PA open standard for media provenance to encode environmental impact metadata. We demonstrate NRGMark on both synthetic and real-world design layouts, illustrating its potential to support energy transparency in the age of GenAI.