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A sub-pixel mapping algorithm based on sub-pixel/pixel spatial attraction models

delete2007-02-22
delete232
PRE
AI
K
Koen Mertens *
B
Bernard De Baets
L
Lieven P. C. Verbeke
DOI：10.1080/01431160500497127delete
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Abstract

Abstract

En 中文
Soft classification techniques avoid the loss of information characteristic to hard classification techniques when handling mixed pixels. Sub-pixel mapping is a method incorporating benefits of both hard and soft classification techniques. In this paper an algorithm is developed based on sub-pixel/pixel attractions. The design of the algorithm is accomplished using artificial imagery but testing is done on artificial as well as real synthetic imagery. The algorithm is evaluated both visually and quantitatively using established classification accuracy indices. The resulting images show increased accuracy when compared to hardened soft classifications.
Keywords:
NEURAL-NETWORK
ARSIS CONCEPT
IMAGE FUSION
COVER
CLASSIFICATION
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

International Journal of Remote Sensing cover
International Journal of Remote Sensing
IF:
2.6
Papers:
1.2W
Citations:
2.7W

Organization

No organization information available