写真測量とリモートセンシング
Online ISSN : 1883-9061
Print ISSN : 0285-5844
最新号
選択された号の論文の17件中1~17を表示しています
巻頭言
カメラアイ
小特集「REDD+におけるリモートセンシングへの期待」
原著論文
  • 須﨑 純一, 岸本 秀真, 田殿 武雄
    2017 年 56 巻 5 号 p. 204-216
    発行日: 2017年
    公開日: 2018/11/01
    ジャーナル フリー

    Advanced Land Observing Satellite (ALOS)/Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) measured triplet images at forward, nadir and backward view directions, and the digital surface model (DSM) is generated from set of triplet images. Existing methods generate multiple DSMs from individual triplet images, and eliminate the effects of outliers by taking average. The proposed method in this paper solves multiple observation equations from all triplet images, and simultaneously determines bias parameters contaminated in the rational polynomial coefficient (RPC) model and ground coordinates. The experimental results showed that errors of the coordinates estimated by using multi-temporal triplet images were almost as small as those estimated with manually determined bias parameters in case of 4 or more sets of triplet images. As a result, we conclude that the proposed method is effective for stably generating accurate DSMs from multi-temporal triplet images.

  • 須﨑 純一, 辻野 雅博, 穴原 琢摩
    2017 年 56 巻 5 号 p. 217-224
    発行日: 2017年
    公開日: 2018/11/01
    ジャーナル フリー

    本論文では,異なる長さの波長を用いて取得された合成開口レーダ(SAR)画像を併用して,高精度に地盤沈下を推定する手法を提案する。差分干渉SAR解析に使用できる画像枚数が少なくなるにつれて,波長が短いSAR画像では位相を復元する際に生じるアンラッピングエラーが発生する可能性が高まる。一方,波長が長いSAR画像では地盤面の小さな変動が検出されにくくなる。提案手法では,まず二種類のSAR画像から個別に変動速度を推定する。次に,類似の変動速度を示す領域のクラスタを個別に生成する。その後,二種類のSAR画像におけるクラスタ間で平均地盤変動速度が一致するように補正を加え,最終的に波長の短いSAR画像によって得られた結果を採用する。提案手法をX,LバンドSARであるTerraSAR-X,PALSAR-2の8枚ずつの画像に適用して,関西国際空港の地盤変動速度を推定した結果,各々の単独解析結果よりも高精度に推定できることが判明した。

  • 近津 博文
    2017 年 56 巻 5 号 p. 225-233
    発行日: 2017年
    公開日: 2018/11/01
    ジャーナル フリー

    Depth of field (DOF) is an important problem in close range photogrammetry, in particular for very small distances between the camera and object. The DOF problem can be resolved by tilting the image sensor with respect to the image plane using a tilt-shift lens based on Scheimpflug condition. Therefore, Scheimpflug cameras mounted with tilt-shift lens have been receiving increasing attention as a potential solution to such a problem. However, conventional calibration models are not valid for Scheimpflug cameras because such models are based on pinhole cameras.

    Thus, a new camera calibration model has been developed for Scheimpflug cameras in this paper using two Scheimpflug angles and a faithful coordinate transformation describing the relationship of a real sensor array plane with respect to an ideal image plane. Experimental results indicate that the proposed calibration model is applicable not only to Scheimpflug cameras but also to conventional pinhole and zoom lens cameras.

  • 薗部 礼, 佐野 智人, 堀江 秀樹
    2017 年 56 巻 5 号 p. 234-243
    発行日: 2017年
    公開日: 2018/11/01
    ジャーナル フリー

    Appearance, aroma and taste are important factors for assessing the quality of tea (Camellia sinensis) and then shading of tea is performed to increase chlorophyll content, which is an important factor for evaluating the appearance and good taste. Although some traditional approaches that require tremendous efforts for the collection of samples and laboratory chemical analyses have been applied, they are not feasible for long-term monitoring. In contrast, hyperspectral remote sensing is proven to be an efficient way for chlorophyll content monitoring. In this study, the three different approaches of kernel-based extreme learning machine (KELM), random forests (RF), and deep belief nets (DBN) were compared to assess the potential for estimating leaf chlorophyll contents from hyperspectral data with existing supervised learning models. Overall, regression models based on KELM yielded the highest performance, achieving a Root Mean Square (RMS) error of 0.20-0.56μg/cm2.

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