Content-Based Image Retrieval Using Angles Across Scales
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS(2022)
摘要
This letter proposes a content-based image retrieval technique using novel dense angle descriptor and dictionary learning (DL). The histogram of oriented gradients (HOG) descriptor fails to obtain rotation invariance and well-defined rotation behavior, and therefore, a dense angle-based HOG descriptor has been presented to address the image rotation invariance. The technique computes angles across multiple scales and uses bag-of-visual features at different scales for DL. Experiments conducted on building and remote sensing datasets show that the proposed technique achieves high retrieval performance.
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关键词
Image retrieval,Visualization,Remote sensing,Dictionaries,Histograms,Feature extraction,Convolutional neural networks,Angle descriptor,dictionary learning (DL),image retrieval
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