Binary Code Reranking Method Based on Bit Importance
Due to its compact binary codes and efficient search scheme, image hashing method is suitable for large-scale image retrieval. In image hashing methods, Hamming distance is used to measure similarity between two points. For K-bit binary codes, the Hamming distance is an into and bounded by K. Therefore, there are many returned images share the same Hamming distances with the query. In this paper, we propose an efficient image ranking method based on bit importance of binary code. Compared with the returned images of Hamming distance, important bits of query image are detected. Then, large weights are assigned to important bits and small weights are assigned to minor bits. The advantage of this proposed method is calculation efficiency. Evaluations on two large-scale image data sets demonstrate the efficacy of our binary code ranking method based on bit importance.