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Journal of Applied Remote Sensing

Visualizing bag-of-words for high-resolution remote sensing image classification
Author(s): Haosong Yue; Weihai Chen; Xingming Wu; Jianhua Wang
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Paper Abstract

Classification of high-resolution remote sensing images is a challenging problem. Bag-of-words (BOW) based classification algorithms have obtained good performances in recent years. However, how the procedures of the BOW framework affect the classification result is still an open question. We present three visualization algorithms to reconstruct images from BOW. After visualization, we can see what the computer actually “sees” in an image feature. We also analyze the procedures of the BOW framework, namely, descriptor extraction and histogram generation, in detail. It is found that the descriptors should not be blamed for wrong classification. The histogram generation strategy should be improved to be robust with image transformation. Then some suggestions are posed for future improvement of BOW-based remote sensing image classification algorithms.

Paper Details

Date Published: 18 March 2016
PDF: 10 pages
J. Appl. Rem. Sens. 10(1) 015022 doi: 10.1117/1.JRS.10.015022
Published in: Journal of Applied Remote Sensing Volume 10, Issue 1
Show Author Affiliations
Haosong Yue, BeiHang Univ. (China)
Weihai Chen, BeiHang Univ. (China)
Xingming Wu, BeiHang Univ. (China)
Jianhua Wang, BeiHang Univ. (China)

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