Performance Analysis of State-of-the-Art Representation Methods for Geographical Image Retrieval and Categorization

This letter studies the performance of various image representation schemes used for image search problems for the purpose of geographic image retrieval from satellite imagery. We compare the most widely adopted method of the bag-of-words (BoW) approach with the more recently introduced vector of locally aggregated descriptors (VLAD) and its more compact binary version product quantized VLAD (VLAD-PQ). We show with the experiments on a publicly available 21-class land-use/land-cover data set that the VLAD-based representation outperforms BoW at the cost of increased query time, but the more compact VLAD-PQ representation achieves very similar performance as VLAD without the increased time requirement.