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논문 기본 정보

자료유형
학술저널
저자정보
Nguyen Quang Minh (Hanoi University of Mining and Geology) Nguyen Thi Thu Huong (Hanoi University of Mining and Geology)
저널정보
한국측량학회 한국측량학회지 한국측량학회지 제31권 제6-2호
발행연도
2013.12
수록면
559 - 565 (7page)

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초록· 키워드

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Spatial resolution of land covers from remotely sensed images can be increased using super-resolution mapping techniques for soft-classified land cover proportions. A further development of super-resolution mapping technique is downscaling the original remotely sensed image using super-resolution mapping techniques with a forward model. In this paper, the model for increasing spatial resolution of remote sensing multispectral image is tested with real SPOT 5 imagery at 10m spatial resolution for an area in Bac Giang Province, Vietnam in order to evaluate the feasibility of application of this model to the real imagery. The softclassified land cover proportions obtained using a fuzzy c-means classification are then used as input data for a Hopfield neural network (HNN) to predict the multispectral images at sub-pixel spatial resolution. The 10m SPOT multispectral image was improved to 5m, 3,3m and 2.5m and compared with SPOT Panchromatic image at 2.5m resolution for assessment.Visually, the resulted image is compared with a SPOT 5 panchromatic image acquired at the same time with the multispectral data. The predicted image is apparently sharper than the original coarse spatial resolution image.

목차

Abstract
1. Introduction
2. General Model
3. Experiment Condition
4. Results and Discussions
5. Conclusions
References

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UCI(KEPA) : I410-ECN-0101-2015-530-001377337