Study about Classification of Multi-Spectral Remote Sensing Images

This paper presents the analogy between voice recognition and multi-spectral remote sensing image classification, and introduces the hidden Markov model (HMM), which is a successful approach on voice recognition fields, into multi-spectral remote sensing image classification. After comparing the HMM with other conventional classification methods such as maximum likelihood and minimum distance, the paper concludes that the HMM is a better approach than other techniques do. At the end of the paper, the author explains the reason of HMM ´ s good performance, and also points out its defect.