We present a scalable registration algorithm for aligning large-frame imagery compressed with the JPEG2000 coding standard. Unlike traditional approaches, the proposed method registers the images in the compressed domain, which eliminates the need to reconstruct the full image prior to performing registration. Two forms of scalability are exploited during registration: resolution and quality. Resolution scalability results from the native multiresolution image representation of the discrete wavelet transform utilized as a building block in JPEG2000. Quality scalability relates to the embedded block coding with optimal truncation (EBCOT) used for compressing the wavelet coefficients. This combination allows registration on selectable resolution levels and quality layers, which enables registration of large-frame imagery at low bit rates over constrained bandwidth channels. Furthermore, the hierarchical nature of the algorithm provides a trade-off between registration accuracy and computational complexity. Experimental results show that the proposed algorithm exhibits consistent registration performance across a range of quality levels (3.5 to 0.5 bpp) for frames sizes of 2 K × 4 K. We present simulation results with imagery collected from a prototype persistent surveillance system to demonstrate the feasibility of the proposed algorithm in real-world scenarios.