Survey of Transform Methods in Remote Sensing Information Processing

摘要

One unique feature in the remote sensing problems is that a significant amount of data are available, from which desired information must be extracted. Transform methods offer effective procedures to derive the most significant information for further processing or human interpretation and to extract important features for pattern classificaiton. In this paper a survey of the use of major transforms in remote sensing is presented. These transforms have significant effects on pattern recognition as features derived from orthogonal or related transforms tend to be very effective for classification, and on data reduction and compression. After the introduction, we will examine the empirical orthogonal function , the discrete Karhunen-Loeve transform and related transforms, the wavelet transform, and the component analysis.