Enhanced Interactive Remote Sensing Image Retrieval with Scene Classification Convolutional Neural Networks Model
Yaakoub Boualleg, Mohamed Farah · 2018
In this paper, we address the semantic gap problem in high-spatial resolution remote sensing images retrieval. We propose a useful semantic image representation that improves the understanding of the machine with respect to the human perception. We use a remote sensing scene classification Convolutional Neural Network (CNN) model to detect the semantic concepts. The similarity distance is calculated to retrieve the most similar images to the given query image. Then, to improve the performance of the retrieval results, a relevance feedback phase has been proposed, which ensures that the final result corresponds to the user need. Our proposal shows promising results and improves the retrieved quality with respect to state-of-the-art approaches.