The traditional model Bag of Words does not capture the spatial relationship among local features

thus affecting the retrieval performance.Hence

the spatial encoding method based on hierarchical salient information is proposed

which aims at fully exploring the geometric context of all visual words in images and increasing the discriminative power of the features based on hierarchical salient information.We propose a new encoding method in the geometric verification step.The spatial layout of every 3 points within a certain salient area will be represented by angle encoding and location encoding

meanwhile we sum all spatial matching scores with weights based on hierarchical salient information to generate the final ranking list.Experimental results prove that our scheme improves the retrieval accuracy significantly and reduces the computing time during the geometric verification step.