Optimized feature space learning for generating efficient binary codes for image retrieval

作者：

Highlights：

• An optimized feature space for single-labeled images by utilizing the relationship between LDA and CCA.

• Extended feature space learning to multi-labeled images with the CCA.

• A novel loss function based on the correlation coefficients of CCA is designed

• An efficient ensemble technique for generating binary codes of desired bit length is proposed

摘要

•An optimized feature space for single-labeled images by utilizing the relationship between LDA and CCA.•Extended feature space learning to multi-labeled images with the CCA.•A novel loss function based on the correlation coefficients of CCA is designed•An efficient ensemble technique for generating binary codes of desired bit length is proposed

论文关键词：Linear Discriminant Analysis,Canonical Correlation Analysis,Hashing,Image retrieval,Iterative Quantization

论文评审过程：Received 21 January 2021, Revised 27 September 2021, Accepted 29 September 2021, Available online 24 October 2021, Version of Record 4 November 2021.

论文官网地址：https://doi.org/10.1016/j.image.2021.116529