A New Self-organization Classification Algorithm for Remote-Sensing Images

摘要

This paper presents a new self-organization clas- sification algorithm for remote-sensing images. Kohonen and other scholars have proposed self-organization algorithms. Ko- honen's model easily converges to the local minimum by tuning the elaborate parameters. In addition to others, S.C. Amatur and Y. Takefuji have also proposed self-organization algorithm model. In their algorithm, the maximum neuron mode (winner- take-all neuron model) is used where the parameter-tuning is not needed. The algorithm is able to shorten the computation time without a burden on the parameter-tuning. However, their model has a tendency to converge to the local minimum eas- ily.