Developing a general post-classification framework for land-cover mapping improvement using high-spatial-resolution remote sensing imagery
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通讯作者 ： 张绪冰
全部作者 ： Lv Z Y, Zhang Xubing*, Benediktsson J
发表刊物 ： Remote Sensing Letters
收录刊物 ： SCI
摘要 ： In this letter, a general post-classification framework (GPCF) is proposed to enhance initial results. Traditional post-classification techniques usually improve classification accuracy by considering the contextual information in a single classified image. In contrast to traditional techniques, the proposed GPCF aims to integrate multi-source classified images obtained through different classification approaches. In the proposed framework, the label of a central pixel is determined by its surrounding voting in each classified image. In this manner, the GPCF can integrate the advantages of dif
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