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Volume 35 (1996)
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Predecessor
Volume 35, Issue 4
Displaying 1-14 of 14 articles from this issue
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[in Japanese]1996 Volume 35 Issue 4 Pages 1
Published: August 30, 1996
Released on J-STAGE: March 19, 2010
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[in Japanese]1996 Volume 35 Issue 4 Pages 2-3
Published: August 30, 1996
Released on J-STAGE: March 19, 2010
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Eihan SHIMIZU1996 Volume 35 Issue 4 Pages 4-8
Published: August 30, 1996
Released on J-STAGE: March 19, 2010
JOURNAL FREE ACCESSLayered feed-forward neural networks (LNNs) have been broadly applied to classification, prediction and other modeling problems. There have been so far, however, few studies that have provided a theoretical interpretation for the application of LNN. Most of the conventional studies have been empirical and the LNNs have been applied just like “black box” machines. This paper discusses the application of LNN to image or remotely sensed data classification. It provides a theoretical interpretation for the LNN classifier in comparison with the conventional classification or discriminant methods. The most distinguished part is the derivation of a generalized form of LNN classifier based on the maximum entropy principle. According to the generalized form, this paper discusses the relationship between the familiar type of LNN classifier employing the sigmoidal activation function and the other types of discriminant models such as the Multinomial Logit Model.View full abstractDownload PDF (548K) -
Yoshiki YAMAGATA, Hiroyuki OGUMA, Hiroko FUJITA1996 Volume 35 Issue 4 Pages 9-17
Published: August 30, 1996
Released on J-STAGE: March 19, 2010
JOURNAL FREE ACCESSWetland monitoring and especially wetland vegetation classification are crucial for preserving valuable wetland ecosystems. The development of remote sensing technique for wetland monitoring is of urgent necessity. In order to improve the accuracy of vegetation classification, we have investigated the wetland vegetation classification using multi-temporal Landsat TM images. Because the growth pattern of a wetland vegetation changes according to the vegetation type, we can used this difference of temporal growth pattern which appear in the multitemporal images for classifying the vegetation types. In order to clarify this temporal growth pattern of wetland vegetation types, we have conducted sampling experiments to measure the biomass growth during the growing season. And also spectral reflectance measurements were conducted to see the spectral difference between the vegetation types as well. As the result of supervised classifications using the multitemporal Landsat TM image, an accurate wetland vegetation classification map has been produced.View full abstractDownload PDF (6661K) -
Hirofumi CHIKATSU, Kazuya NAKANO1996 Volume 35 Issue 4 Pages 18-26
Published: August 30, 1996
Released on J-STAGE: March 19, 2010
JOURNAL FREE ACCESSIn general, recording for archeological sites is performed by plane table surveying, leveling or section drawing, expending a great deal of time and labor. Digital photogrammetry is expected to become a useful tool in this field. However, time consumed in geodetic surveying for camera calibration is still an issue which needs to be resolved. By using information such as distance which is included in the image as proposed in this paper, time consuming aspects of geodetic surveying can be improved.
This paper describes on a real-time photogrammetric system for site recording by using wireless CCD camera.View full abstractDownload PDF (8886K) -
Hirofumi CHIKATSU, Tetsuji ANAI, Shunji MURAI1996 Volume 35 Issue 4 Pages 27-36
Published: August 30, 1996
Released on J-STAGE: March 19, 2010
JOURNAL FREE ACCESSGenerally, a dynamic analysis of human motion has been performed under a condition that camera position and rotation are fixed and some markers are fitted on the body. Therefore, it is possible to calibrate the camera parameters in advance. Also, automated recognition of some human feature points such as the head, elbow or knees is possible. In order to understand a dynamic analysis of the most natural human motion, limitation of the camera and any marker on the body should be removed. For this ideal dynamic analysis, however, camera orientation parameters should be acquired in real time while recording a moving object. Furthermore, automated recognition of some human feature points should be performed.
The effectiveness of the video theodolite system for dynamic analysis of human motion has been indicated by the authors. This paper describes the dynamic analysis of human motion using sequential images which are taken by video theodolite. Also, image processing techniques are described.View full abstractDownload PDF (8953K) -
Kotoyo TANIGUCHI1996 Volume 35 Issue 4 Pages 37-39
Published: August 30, 1996
Released on J-STAGE: March 19, 2010
JOURNAL FREE ACCESSCanopy reflectance model is a useful tool to correct the effect of measuring conditions like as the changes in observation angle and solar irradiance angle. So that, if we use the corrected reflectance data by the model for estimating vegetation index such as NDVI, we can derive more accurate information of vegetative distribution from satellite data.
Nowadays, the famous model for canopy reflectance is the SAIL model. (Verhoef, 1984) This study notices that the leaf reflectance parameter of the SAIL model is considered only front surface of leaves. And so, we survey the influence on canopy reflectance. As a result of it, we find that it is not adequate to predict canopy reflectance by using only front surface reflectance of leaves.View full abstractDownload PDF (380K) -
Atushi IWASHITA, Yoshiaki MATSUMAE1996 Volume 35 Issue 4 Pages 40-44
Published: August 30, 1996
Released on J-STAGE: March 19, 2010
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Yuichi MARUYAMA, Hiroji TSU1996 Volume 35 Issue 4 Pages 45-49
Published: August 30, 1996
Released on J-STAGE: March 19, 2010
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Hideo TAMEISHI1996 Volume 35 Issue 4 Pages 50-52
Published: August 30, 1996
Released on J-STAGE: March 19, 2010
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Zhongchao SHI, Ryosuke SHIBASAKI1996 Volume 35 Issue 4 Pages 53-58
Published: August 30, 1996
Released on J-STAGE: March 19, 2010
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[in Japanese]1996 Volume 35 Issue 4 Pages 59-61
Published: August 30, 1996
Released on J-STAGE: March 19, 2010
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[in Japanese]1996 Volume 35 Issue 4 Pages 62-64
Published: August 30, 1996
Released on J-STAGE: March 19, 2010
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[in Japanese]1996 Volume 35 Issue 4 Pages 65
Published: August 30, 1996
Released on J-STAGE: March 19, 2010
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