title: Scene-Level Geographic Image Classification Based on a Covariance Descriptor Using Supervised Collaborative Kernel Coding.
abstract: Scene-level geographic image classification has been a very challenging problem and has become a research focus in recent years. This paper develops a supervised collaborative kernel coding method based on a covariance descriptor (covd) for scene-level geographic image classification. First, covd is introduced in the feature extraction process and, then, is transformed to a Euclidean feature by a supervised collaborative kernel coding model. Furthermore, we develop an iterative optimization framework to solve this model. Comprehensive evaluations on public high-resolution aerial image dataset and comparisons with state-of-the-art methods show the superiority and effectiveness of our approach.
authors.affiliation: High-Tech Institute of Xi'an, Xi'an 710025, China. yangchunwei081129@163.com.|Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China. yangchunwei081129@163.com.
authors.forename: Chunwei
authors.initials: C
authors.lastname: Yang
authors.affiliation: Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China. hpliu@tsinghua.edu.cn.
authors.forename: Huaping
authors.initials: H
authors.lastname: Liu
authors.affiliation: High-Tech Institute of Xi'an, Xi'an 710025, China. wangsching@163.com.
authors.forename: Shicheng
authors.initials: S
authors.lastname: Wang
authors.affiliation: High-Tech Institute of Xi'an, Xi'an 710025, China. liaoshouyi123@163.com.
authors.forename: Shouyi
authors.initials: S
authors.lastname: Liao
keywords: collaborative kernel coding; covariance descriptor; scene-level geographic image classification