We propose an image fusion method robust to misaligned source images based on their multiscale edge representations. Significant long edge curves at the second scale are selected to decide edge locations at each scale for the multiscale edge representations of source images. Then, processes are only executed on the representations that contain the main spatial structures of the images and also help suppress noise interference. A registration process is embedded in our fusion method. Edge correlation, calculated at the second scale, is involved as a match measure determining the fusion rules and also as a similarity measure quantifying the matching extent between source images, which makes the registration and fusion processes share the same data and hence lessens the computation of our method. Experimental results prove that, no matter whether in a noiseless or noisy condition, the proposed method provides satisfying treatment to misregistered source images and behaves well in terms of visual and objective evaluations on the fusion results, which further verifies the robustness of our edge-based method to misregistration and noise.