The main obstacle to realize real semantic-based image retrieval is that semantic description of versatile images is difficult. The basic ideas of this paper are that the semantics of an object can be refined through top–down orthogonal semantic classification and that the semantics of an object can be reflected by the semantics of relevant objects and the semantic relationships between them. T...

Unsupervised hashing methods have attracted considerable attention in large-scale remote sensing (RS) image retrieval, due to their capability for massive data processing with significantly reduced storage and computation. Although existing unsupervised are suitable operational applications, they exhibit limitations when accurately modeling the complex semantic content present RS images using b...

The state-of-the-art image retrieval approach is to incorporate image semantics with low-level features to enhance retrieval performance. Although many systems annotate images with descriptive keywords and retrieve images by keyword-based search, they have not explored the full potentials of semantics. This paper exploits the power of thesaurus-aided approaches to facilitate semantics-based acc...