Coarse-Fine classification of landsat image
using Neural Network
Kozo Okazaki*, Yutaka Fukui*, Yoshihiro Nobuoka*,
Hiroshi Mitsumoto**,
Shinichi Tamura***, Guo-Fang Shi***
*Faculty of Engineering, Tottori University
**Faculty of Engineering Science, Osaka University
***Osaka University Madical School
Takashi Hoshi+, Kiyoshi Torii++
+Institute of Information Sciences and
Electronics
University of Tsukuba
++ Faculty of Agriculture, Kyoto University
Abstract
We have already presented a neural approach to the landsat window image classification by personnal computer based system. Here, we used a 32 bit personal computer (NEC PC-9801 RA) , Hyper frame board memory (HFBM,3 planes) and Image Pipeline Processing (Im PP) board. In this case, however, the classification is often rough in some areas. If we make the size of window smaller in order to resolve this, we need much more time for processing. Considering the classification, a larger window is reasonable for a region such as sea, lake, etc. and a smaller window is suitable for a compound area.
In this paper, we propose a method of coarse-fine classification of landsat image using error back propagation algorithm (BP), where we used several sizes of windows. Furthermore, we made up the software of using two HFBMs and applied them to BP for processing the 4ch. image data. .
Introduction
We have propose a neural network approach to the remote sensing image data [1]. Here, multi-channel image data composed of neighboring pixels are used as input to the back propagation network. The training is done by error back propagation (BP) algorithm.
The classification of multi-spectral remote sensing image is, usually, based on multi-variable analysis. This method examines the statistical characteristics for every pixels. Generally, the image shows a marked trend of being classified excessively. However, classifications of he ample flat area including sea, lake area, etc. need to use more large regions for processing. This paper deals with a method of coarse-fine classification of landsat image using BP, where we use several sizes of windows. Furthmore, we made up the software of using two HFBMs and applied them to BP for processing the 5ch . image data. .
System configuration
We used a personal computer based system; computer (NEC PC9801 RA), ImPP neural board (NEC), Neuro07 software (NEC Information Technology Co. Ltd.), Hyper Frame (Digital Arts Co. Ltd.) and 80387 co-processor (Fig. 1). The classification of image is carried out at high speed by ImPP and co-processor. Usually, one HFBM (64x400pixelx3plane) is used. We made up the software of using two (three or four boards are possible as well) HFBMs. We can process the six landsat channels data as the maximum.
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Fig. 1 System Configuration by personal computer
