Jointly sparse fast hashing with orthogonal learning for large-scale image retrieval

Honghao Xu, Zhihui Lai, Heng Kong

Abstract: Highlights•The jointly sparse feature extraction with orthogonal constraint is designed for hash learning.•We design an iterative algorithm to optimize the model with closed-form solutions with less information loss.•The proposed JSFH is evaluated on four large-scale datasets.