A Simplified Approach for Interpreting Principal Component Images

• 作者: Neeraj Srivastava Ravi P. Gupta Reet K. Tiwari Varinder Saini
• 来源期刊: 遥感技术进展(英文)
• 学科: 数学
• 关键词: Principal Component IMAGES REMOTE SENSING EIGENVECTORS SPECTRAL Behavior
• 年，卷（期）: 2013,（2）
• 页码范围: 111-119
• 页数: 9页
• 分类号: O1

摘要

Principal component transformation is a standard technique for multi-dimensional data analysis. The purpose of the present article is to elucidate the procedure for interpreting PC images. The discussion focuses on logically explaining how the negative/positive PC eigenvectors (loadings) in combination with strong reflection/absorption spectral behavior at different pixels affect the DN values in the output PC images. It is an explanatory article so that fuller potential of the PCT applications can be realized.