Spectral unmixing aims at finding the spectrally pure constituent materials (also called endmembers) and their respective fractional abundances in each pixel of the hyperspectral image scene. One important issue in hyperspectral data unmixing is the initialization of endmembers. Most unmixing methods initialize their endmembers by randomly selecting a specified number of pixels from the data or by vertex component analysis, which limits their performance in practice. We propose an endmember initialization method for hyperspectral data unmixing. Our initial endmembers include some of the true endmembers, which improves the accuracy of hyperpspectral unmixing effectively. The experimental results on both synthetic and real hyperspectral data illustrate the superiority of the proposed method compared with other state-of-the-art approaches.