Since there are few open image retrieval toolkits available, researchers in the field are often forced to re-implement existing algorithms in order to perform a comparative evaluation. None of the existing toolkits support retrieval of JPEG images directly in the compressed domain. The authors’ aim is therefore to facilitate the use of compressed domain image retrieval techniques as well as ease retrieval evaluation by fellow researchers. For this purpose, the authors present JIRL, an open source C++ software suite that allows content-based image retrieval in the JPEG compressed domain and provides tools for benchmarking retrieval accuracy and retrieval time. In total, twelve state-of-the-art JPEG retrieval algorithms are implemented, while for each method techniques for compressed domain feature extraction as well as feature comparison are provided in an object-oriented framework. An example image retrieval application is also provided to demonstrate how the library can be used. JIRL is made available to fellow researchers under the LGPL v.2.1 license.
A novel coarse-to-fine remote sensing image retrieval system in JPEG-2000 compressed domain