A retrieval method based on the fusion of Bag of Visual Words (BoVW) and Gabor texture is presented for the high resolution remote sensing images. Remote sensing images have rich texture information and many local key points. But when an image contains lots of similar texture, the retrieval precision of BoVW will be reduced. The fusion of BoVW and Gabor texture combines the advantages of local feature and global feature, mid-level feature and low-level texture to improve image description. Experiment results show that the presented fusion method is superior to the traditional fusion method using Gabor texture and color moments. Retrieval performance of the fused features method is improved compared with that using single feature, and the improved performance depended on the suitable fusion weights. Experiment results indicate that the fused BoVW and Gabor texture is effective for high-resolution remote sensing image retrieval.