写真測量とリモートセンシング
Online ISSN : 1883-9061
Print ISSN : 0285-5844
検索
OR
閲覧
検索
54 巻 , 6 号
選択された号の論文の9件中1~9を表示しています
    • |<
    • <
    • 1
    • >
    • >|
巻頭言
カメラアイ
小特集「インフラ構造物のモニタリング」
原著論文
  • 松岡 真如, 本田 理恵, 野々村 敦子, 守屋 均, 赤塚 慎, 吉岡 博貴, 高木 方隆
    54 巻 (2015) 6 号 p. 280-289
    公開日: 2017/01/01
    ジャーナル フリー
    This study proposed a method to improve the geometric accuracy of the Advanced Himawari Imager (AHI), an instrument on board the recently launched Himawari-8 spacecraft, focusing on the data set over Japan acquired in the regional acquisition mode. The AHI scanning mechanism consists of four west-east horizontal sweeps, and derived four sub-images are combined into a single dataset. This scanning mechanism gives rise to variations in geometric accuracy among the four sub-images. These variations were quantified by analyzing the AHI band-3 images, which has the highest spatial resolution (0.5km) among the AHI bands. The geometric error, determined as the root mean square of average errors in each scan, was found to be approximately 0.3 pixels in the vertical (north-south) direction and 1 pixel in the horizontal direction during 8 hours of daytime. The geometric error showed two characteristics : temporal fluctuation, and variation by the scan. This study proposes a technique to improve these ‘scan-dependent' geometric errors by shifting the four sub-images independently based on the average error in each scan. The proposed method successfully reduced the geometric errors to 0.07 pixels in the vertical and 0.15 pixels in the horizontal direction, and hence improved the quality of time series composite images obtained using the AHI. Such geometrically-improved AHI image would enhance the accuracies of multi-temporal analyses used in the monitoring of vegetation, land use/land cover change, disasters and so on.
    抄録全体を表示
  • 布施 孝志, 松本 圭生
    54 巻 (2015) 6 号 p. 290-299
    公開日: 2017/01/01
    ジャーナル フリー
    Development of high performance CPU, cameras and other sensors on mobile devices have been used for wide variety of applications. The applications require self-localization of the devices. Since the self-localization is based on GPS, gyro sensor, acceleration meter and magnetic field sensor (POS) of low accuracy, the applications are limited. On the other hand, self-localization method using images have been developed, and the accuracy of the method is increasing. This paper develops the self-localization method by integrating sensors, such as POS and a camera on a mobile device. The proposed method mainly consists of two parts : one is the accuracy improvement of POS data with filtering, and another is development of self-localization method by integrating POS data and images. The POS data filtering combines all data by using Kalman filter. The estimated exterior orientation factors are used as initial value of ones in image-based self-localization method, which is based on structure from motion. The exterior orientation factors are integrated and updated by applying bundle adjustment. Through experiments with real data, the accuracy improvement by the proposed method is confirmed.
    抄録全体を表示
研究速報
    • |<
    • <
    • 1
    • >
    • >|
feedback
Top