Dr. Tao Guo Profile

Dr. Tao Guo

at Hitachi Ltd

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Publications (8)

Proceedings Article | 18 November 2014 Paper

Satellite image time series simulation for environmental monitoring

Tao Guo

Proceedings Volume 9263, 926303 (2014) https://doi.org/10.1117/12.2069460

KEYWORDS: Image resolution, Temporal resolution, Spatial resolution, Satellites, Satellite imaging, Data modeling, Environmental monitoring, Earth observing sensors, Image registration, Remote sensing

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The performance of environmental monitoring heavily depends on the availability of consecutive observation data and it turns out an increasing demand in remote sensing community for satellite image data in the sufficient resolution with respect to both spatial and temporal requirements, which appear to be conflictive and hard to tune tradeoffs. Multiple constellations could be a solution if without concerning cost, and thus it is so far interesting but very challenging to develop a method which can simultaneously improve both spatial and temporal details. There are some research efforts to deal with the problem from various aspects, a type of approaches is to enhance the spatial resolution using techniques of super resolution, pan-sharpen etc. which can produce good visual effects, but mostly cannot preserve spectral signatures and result in losing analytical value. Another type is to fill temporal frequency gaps by adopting time interpolation, which actually doesn't increase informative context at all. In this paper we presented a novel method to generate satellite images in higher spatial and temporal details, which further enables satellite image time series simulation. Our method starts with a pair of high-low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and the temporal change is then projected onto high resolution data plane and assigned to each high resolution pixel referring the predefined temporal change patterns of each type of ground objects to generate a simulated high resolution data. A preliminary experiment shows that our method can simulate a high resolution data with a good accuracy. We consider the contribution of our method is to enable timely monitoring of temporal changes through analysis of low resolution images time series only, and usage of costly high resolution data can be reduced as much as possible, and it presents an efficient solution with great cost performance to build up an economically operational monitoring service for environment, agriculture, forest, land use investigation, and other applications.

Proceedings Article | 23 October 2014 Paper

A method for generating high-resolution satellite image time series

Tao Guo

Proceedings Volume 9244, 924404 (2014) https://doi.org/10.1117/12.2067577

KEYWORDS: Image resolution, Temporal resolution, Spatial resolution, Satellites, Data modeling, Image registration, Remote sensing, Agriculture, Satellite imaging, Earth observing sensors

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There is an increasing demand for satellite remote sensing data with both high spatial and temporal resolution in many applications. But it still is a challenge to simultaneously improve spatial resolution and temporal frequency due to the technical limits of current satellite observation systems. To this end, much R&D efforts have been ongoing for years and lead to some successes roughly in two aspects, one includes super resolution, pan-sharpen etc. methods which can effectively enhance the spatial resolution and generate good visual effects, but hardly preserve spectral signatures and result in inadequate analytical value, on the other hand, time interpolation is a straight forward method to increase temporal frequency, however it increase little informative contents in fact. In this paper we presented a novel method to simulate high resolution time series data by combing low resolution time series data and a very small number of high resolution data only. Our method starts with a pair of high and low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and then projected onto the high resolution data plane and assigned to each high resolution pixel according to the predefined temporal change patterns of each type of ground objects. Finally the simulated high resolution data is generated. A preliminary experiment shows that our method can simulate a high resolution data with a reasonable accuracy. The contribution of our method is to enable timely monitoring of temporal changes through analysis of time sequence of low resolution images only, and usage of costly high resolution data can be reduces as much as possible, and it presents a highly effective way to build up an economically operational monitoring solution for agriculture, forest, land use investigation, environment and etc. applications.

Proceedings Article | 3 June 2014 Paper

A robust method for online stereo camera self-calibration in unmanned vehicle system

Yu Zhao, Nobuhiro Chihara, Tao Guo, Nobutaka Kimura

Proceedings Volume 9084, 90840T (2014) https://doi.org/10.1117/12.2051005

KEYWORDS: Calibration, Cameras, Imaging systems, Stereoscopic cameras, Unmanned systems, Unmanned vehicles, Evolutionary algorithms, Detection and tracking algorithms, Roads, Global Positioning System

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Self-calibration is a fundamental technology used to estimate the relative posture of the cameras for environment recognition in unmanned system. We focused on the issue of recognition accuracy decrease caused by the vibration of platform and conducted this research to achieve on-line self-calibration using feature point's registration and robust estimation of fundamental matrix. Three key factors in this respect are needed to be improved. Firstly, the feature mismatching exists resulting in the decrease of estimation accuracy of relative posture. The second, the conventional estimation method cannot satisfy both the estimation speed and calibration accuracy at the same tame. The third, some system intrinsic noises also lead greatly to the deviation of estimation results. In order to improve the calibration accuracy, estimation speed and system robustness for the practical implementation, we discuss and analyze the algorithms to make improvements on the stereo camera system to achieve on-line self-calibration. Based on the epipolar geometry and 3D images parallax, two geometry constraints are proposed to make the corresponding feature points search performed in a small search-range resulting in the improvement of matching accuracy and searching speed. Then, two conventional estimation algorithms are analyzed and evaluated for estimation accuracy and robustness. The third, Rigorous posture calculation method is proposed with consideration of the relative posture deviation of each separated parts in the stereo camera system. Validation experiments were performed with the stereo camera mounted on the Pen-Tilt Unit for accurate rotation control and the evaluation shows that our proposed method is fast and of high accuracy with high robustness for on-line self-calibration algorithm. Thus, as the main contribution, we proposed methods to solve the on-line self-calibration fast and accurately, envision the possibility for practical implementation on unmanned system as well as other environment recognition systems.

Proceedings Article | 9 November 2012 Paper

A method for enhancing spectral resolution of multispectral satellite imagery

Tao Guo, Toshihiro Kujirai, Takashi Watanabe, Yu Kitano, Yu Zhao

Proceedings Volume 8527, 85270C (2012) https://doi.org/10.1117/12.975792

KEYWORDS: Sensors, Satellites, Satellite imaging, Earth observing sensors, Spectral resolution, Image enhancement, Reflectivity, Super resolution, Resolution enhancement technologies, Multispectral imaging

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Proceedings Article | 23 October 2010 Paper

House damage assesment based on supervised learning method: case study on Haiti

Yoriko Kazama, Tao Guo

Proceedings Volume 7830, 78301F (2010) https://doi.org/10.1117/12.867699

KEYWORDS: Earthquakes, Satellites, Satellite imaging, Earth observing sensors, Machine learning, Vegetation, Target detection, Buildings, Data acquisition, Raster graphics

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Proceedings Article | 23 October 2010 Paper

Towards automation of building damage detection using WorldView-2 satellite image: the case of the Haiti earthquake

Tao Guo, Yoriko Kazama

Proceedings Volume 7831, 783108 (2010) https://doi.org/10.1117/12.867232

KEYWORDS: Earthquakes, Image segmentation, Satellites, Damage detection, Earth observing sensors, Satellite imaging, Machine learning, High resolution satellite images, Feature extraction, Data modeling

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Proceedings Article | 28 September 2009 Paper

Automatic house detection from high-resolution satellite imagery

Yoriko Kazama, Tao Guo

Proceedings Volume 7477, 747710 (2009) https://doi.org/10.1117/12.829721

KEYWORDS: Principal component analysis, Satellite imaging, Earth observing sensors, Satellites, Target detection, Target recognition, Machine learning, Algorithm development, Wavelets, Sun

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Proceedings Article | 11 June 2003 Paper

Data fusion of high-resolution satellite images and airborne laser scanning data for building detection in an urban environment

Tao Guo, Yoshifumi Yasuoka

Proceedings Volume 4898, (2003) https://doi.org/10.1117/12.467390

KEYWORDS: Earth observing sensors, High resolution satellite images, Satellites, Satellite imaging, Image fusion, Airborne laser technology, Data fusion, Data modeling, 3D modeling, 3D image processing

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Showing 5 of 8 publications

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