A Selection Criterion for the Optimal Resolution of Ground-Based Remote Sensing Cloud Images for Cloud Classification | |
Wang Y(王钰); Wang CH(王春恒); Shi CZ(史存召); Xiao BH(肖柏华) | |
发表期刊 | IEEE Transactions on Geoscience and Remote Sensing |
2019 | |
期号 | 3页码:1358-1367 |
摘要 | In ground-based remote sensing cloud image observation, images with the highest possible resolution are captured to obtain sufficient information about clouds. However, when features are extracted and classification is performed on the basis of the original images, a high-resolution probably means a high (or even more, unacceptable) computation cost. In practical application, a simple and commonly adopted method is to appropriately resize the original image to a version with a decreased resolution. An inevitable problem is whether useful information is lost in this resizing operation. This paper demonstrates that information loss is inevitable and poor classification results may be obtained from the analysis of local binary pattern (LBP) histogram features. However, this problem has been always neglected in previous studies, and the original image is arbitrarily resized without any criterion. In particular, the histogram features based on LBPs actually reflect the distribution of features. Thus, a criterion based on the Kullback–Leibler divergence between LBP histograms from the original and resized images and a penalty term imposed on the resolution are proposed to select the resolution of the resized image. The optimal resolution of the resized image can be selected by minimizing this criterion. Furthermore, experiments based on three ground-based remote sensing cloud image data sets with different original resolutions validate this criterion by analyzing the LBP histogram features. |
关键词 | Cloud Image Classification Local Binary Patterns Resolution Selection Kullback– Leibler (Kl) Divergence |
收录类别 | SCI |
WOS记录号 | WOS:000460321300011 |
七大方向——子方向分类 | 图像视频处理与分析 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/23629 |
专题 | 复杂系统管理与控制国家重点实验室_影像分析与机器视觉 |
作者单位 | 中国科学院自动化研究所 |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Wang Y,Wang CH,Shi CZ,et al. A Selection Criterion for the Optimal Resolution of Ground-Based Remote Sensing Cloud Images for Cloud Classification[J]. IEEE Transactions on Geoscience and Remote Sensing,2019(3):1358-1367. |
APA | Wang Y,Wang CH,Shi CZ,&Xiao BH.(2019).A Selection Criterion for the Optimal Resolution of Ground-Based Remote Sensing Cloud Images for Cloud Classification.IEEE Transactions on Geoscience and Remote Sensing(3),1358-1367. |
MLA | Wang Y,et al."A Selection Criterion for the Optimal Resolution of Ground-Based Remote Sensing Cloud Images for Cloud Classification".IEEE Transactions on Geoscience and Remote Sensing .3(2019):1358-1367. |
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