Object-oriented classification of high-resolution remote sensing imagery based on an improved colour structure code and a support vector machine

By Haitao Li, Haiyan Gu, Yanshun Han, Jinghui Yang. 2010

96 citations recorded by the source corpus.

Subfields: Atmospheric Science, Computer Vision and Pattern Recognition, Ecology, Media Technology, Remote Sensing

Citations in the corpus

• Strathprints Institutional Repository Shuhui and Ren, Jinchang (2015) Effective and Efficient Midlevel Visual Elements-oriented Land-use Classification Using Vhr Remote Sensing Images. Ieee Transactions on Geoscience and Remote Sensing, 53 (8). Pp. 4238-4249. Issn 0196-2892 Effective and Efficient M (unknown): “Most previous works [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] mainly focus on classifying pixels or objects (or rather, grouping of local homogeneous pixels) into their thematic class by extracting low-level image features (e.g. texture feature [9] [10], color feature [8], spatial and…”
• Support vector machines in remote sensing: A review (2011, unknown): “Starting with high resolution imagery, Li et al. (2010) proposed an SVM-based classifier using QuickBird data.”