Motion-compensated temporal filtering (MCTF) is an open-loop prediction scheme, so the frame-level data reuse for MCTF is possible. In this paper, we propose two general frame-level data reuse schemes which can minimize the memory bandwidth of current and reference frames, respectively. And their relationships between the required memory bandwidth and the number of searching range buffers are also formulated under the constraint of the data dependency in joint scalable video model. Finally, we extend our analysis to pyramid MCTF and the impact of the inter-layer prediction scheme is also considered.